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DESIGN & IMPLEMENTATION OF BIOMEDICAL DEVICES FOR EVALUATION &
REHABILITATION HIGHLIGHTING RAPID PROTOTYPING TOOLS & PROCESSES
A Thesis Presented
by
Richard Gabriel Ranky
to
The Department of Mechanical Engineering
in partial fulfillment of the requirements for the degree of
Master of Science
in
Mechanical Engineering
In the field of
Mechanics and Design
Northeastern University Boston, Massachusetts
August 2009
Abstract Developments in non-invasive three-dimensional scanning have made it possible to
acquire digital models of freeform surfaces typical of the human body. Combined with
rapid prototyping (RP) techniques, these technologies have the potential to transform
personal medical devices by streamlining fabrication and providing a quantitative means
to monitor patient physiology.
The medical orthotics field contains opportunities for streamlining and improving the
process for fitting a patient-specific ankle-foot orthoses (AFO). A novel process
architecture was developed to utilize 3D photogrammetric scanning as the patient-
specific form data input, and selective laser sintering (SLS) as the patient-specific RP
form output ideally suited for medical orthoses where form fit and comfort are
paramount. Gait analysis proved that the ambulatory dynamics of the SLS AFO can
match the capabilities of comparable polypropylene devices for impact on gait of a
healthy subject.
RP with instrumented assemblies were used to design a system to simultaneously
improve cardiovascular ability, neuromuscular endurance, and fine motor control for
patients post-stroke by training them in a safe seated position on a stationary exercise
bike. Modular sub-systems monitored physiological parameters in the upper and lower
extremities via instrumented handlebars and pedals, which provide input controls to the
patient’s cyclist avatar in a virtual rehabilitation environment.
Together these technologies address mass-customization of intelligent medical
mechatronic devices to remotely sense, evaluate, and rehabilitate patient populations with
neuromuscular & musculoskeletal deficits.
ii
Acknowledgement
I would like to begin by acknowledging my adviser, Dr. Constantinos Mavroidis. I am
grateful for the experience and skills gained by being taken on as one of his researchers,
and for his many hours of council and wisdom. The research undertaken here has allowed
me to have a very fulfilling and uniquely interdisciplinary graduate experience at
Northeastern.
Thank you to the band of brothers in the Biomedical Mechatronics Laboratory. It was
already a great honor to be part of the lab, but their inspiration, support, and sense of
humor made it a great experience to be part of the team. Especially thank you to our lab
manager, Brian Weinberg whose amazing talent to solve engineering mistakes is only
rivaled by his ability to forgive people for them. Each project here has succeeded largely
thanks to his help.
This work is presented with great appreciation for Dr. Paolo Bonato & the Motion
Analysis Laboratory for their professionalism and encyclopedic biomechanics expertise.
Bill Cusack spent many late nights and early morning helping to strive through the ramp
project, and right to the end preventing the walkway from going all pear-shaped.
I would like to also express my gratitude to Mr. Bob Drillio, Certified Orthotist of IAM
Orthotics & Prosthetics, Inc of Wellesley, MA for providing invaluable insight and
advising for the orthotics treatment process, application, and evaluations.
iii
Dedication
I am thankful for cheers from my friends, Carly from snowy mountains in Colorado,
encouragement from the At-Cave, or the mystical, magical realms of New Jersey, as well
as the future occupants of Gundam silo 812: Frank, Mark, and Jay. Thank you to my
wonderful Caryn, for your patience and loving words of confidence throughout long
nights and weekends. I cherish you all and am truly fortunate to have you in my life.
I would like to dedicate this work to my caring & supportive family: Mum, Dad, & Greg,
who have been an inspiration and pillar of strength in my life. I could not have made it to
this point without their love, guidance, and limitless supplies of chowder and carrot cake
in addition to a warm bed at home.
For my father who showed me how a dedicated engineer improves the world
For my mother who showed me the value of patience and courage above all
For my brother who taught me how to find blue sky in a basement
iv
Table of Contents
Abstract _______________________________________________________________ i
Acknowledgement ______________________________________________________ ii
Dedication _____________________________________________________________ iii
List of Figures __________________________________________________________ vi
List of Tables ___________________________________________________________ xii
1.0 Introduction _____________________________________________________ 1
1.1 Goal & Motivation ____________________________________________________ 1
1.2 Thesis Organization ____________________________________________________ 2
2.0 Background ______________________________________________________ 3
2.1 Ankle‐Foot Anatomy ___________________________________________________ 3
2.2 Incline Gait __________________________________________________________ 4
2.3 Current Corrective Rehabilitation Methods ________________________________ 9
2.4 Freeform Surface Capture Using 3D Scanning ______________________________ 18
2.5 Rapid Prototyping Techniques __________________________________________ 22
3.0 Patient‐Specific Ankle‐Foot Orthoses Using Rapid Prototyping & 3D Scanning 30
3.1 Process Overview ____________________________________________________ 30
3.2 Medical Applications & Prior Art ________________________________________ 32
3.3 Existing Custom AFO Process ___________________________________________ 34
3.4 Digital Custom AFO Process ____________________________________________ 38
3.5 Comparative Testing for AFO Gait Analysis ________________________________ 61
3.6 Analysis & Discussion _________________________________________________ 68
3.7 Conclusions & Future Work ____________________________________________ 71
4.0 Modular Stationary Bicycle Kit for Evaluation & Treatment of Patients Post‐Stroke 72
v
4.1 System Overview ____________________________________________________ 72
4.2 Medical Applications & Prior Art ________________________________________ 75
4.3 Design & Sub‐Systems ________________________________________________ 90
4.4 Testing & Experimental Setup _________________________________________ 121
4.5 Data ______________________________________________________________ 128
4.6 Analysis & Discussion ________________________________________________ 138
4.7 Conclusions & Future Work ___________________________________________ 148
5.0 CONCLUSION ___________________________________________________ 152
APPENDIX A: Custom AFO Detailed Process ________________________________ 153
APPENDIX B: RP Materials Detailed Comparison ____________________________ 160
APPENDIX C: Genex Facecam 3D Scan Accuracy _____________________________ 164
APPENDIX D: Chapter 4.0 Bill of Materials _________________________________ 166
APPENDIX E: Adjustable Ramp for Incline Gait Analysis ______________________ 167
E.1 Device Overview _______________________________________________________ 167
E.2 Incline Gait Analysis Systems _____________________________________________ 168
E.3 Design & Sub‐Assemblies ________________________________________________ 169
REFERENCES ______________________________________________________________ 176
vi
List of Figures
Figure 1: Ankle‐Foot anatomical bone structure [7] ........................................................................................ 3
Figure 2: Ankle‐Foot joints of major functional significance [7] ...................................................................... 4
Figure 3: Comparison of angular kinematics and lower extremity joints during level and downhill (‐19°
gradient) walking averages for 12 subjects [11] ............................................................................................. 6
Figure 4: Comparison of vertical and horizontal ground reaction forces from an embedded force plate
during level and downhill (‐19° gradient) gait averaged for 12 subjects [11] ................................................. 7
Figure 5: Comparison of net joint moments for the lower extremities during level and downhill (‐19%
gradient) gait averaged for 12 subjects [11] ................................................................................................... 8
Figure 6: Gait Walkway in Motion Analysis Laboratory, Spaulding Hospital, Boston, MA. A)Vicon motion
capture system, B) Force pads for recording ground reaction forces, C) Instrumented level walkway, D)
Practitioner preparation area........................................................................................................................ 10
Figure 7: Reflective marker locations on lower extremities .......................................................................... 11
Figure 8: Gait analysis using infra‐red motion capture for joint kinematic and force plates for ground
reaction forces[15] ........................................................................................................................................ 12
Figure 9: Bi‐layer instep pediatric AFO with shell material removed to accommodate bony protuberances
held in silicone ............................................................................................................................................... 14
Figure 10: Jointed pediatric AFO with foot insert for patient with high tone in ankle‐foot complex. Inner
boot is comprised of modified polyethylene. ................................................................................................. 14
Figure 11: Rigid pediatric AFO with plaster zoat, peelite, and alliplast inner linings .................................... 14
Figure 12: Articulated Crouch Walker AFO for controlled dorsiflexion .......................................................... 15
Figure 13: Muscleature and movements required for healthy cycling [26] ................................................... 16
Figure 14: Average normal and tangential components of pedal loading recorded during cycling at 350W,
90 rpm (n = 17 riders). Crank angle 0 & 360 corresponds to Top Dead Center [27] ...................................... 17
Figure 15: Konica Minolta Vivid 910 Laser scanner ....................................................................................... 20
Figure 16: Stereolithography build process [34] ............................................................................................ 24
vii
Figure 17: Bordering, hatching, and filling for one square [33]..................................................................... 24
Figure 18: Fused Deposition Modeling Process [34] ...................................................................................... 25
Figure 19: Fused deposition modeling contour and raster path for circular cross‐section [33] .................... 26
Figure 20: Selective Laser Sintering Process [35] ........................................................................................... 28
Figure 21: Patient‐Specific AFO overview ...................................................................................................... 30
Figure 22: Existing process documentation for custom AFO evaluation, fitting, and fabrication ................. 34
Figure 23: Existing process schematic for custom AFO evaluation, fitting, and fabrication ......................... 36
Figure 24: Digital custom AFO process .......................................................................................................... 38
Figure 25: Examples of anomalies and inconsistencies with scanning skin for faces and right arm ............. 43
Figure 26: Visual difference in scan quality for bare skin and nylon covered surfaces .................................. 44
Figure 27: Matte & glossy sample scans of square and cylindrical cross‐section ......................................... 47
Figure 28: Digital processes flow diagram for point cloud refinement ......................................................... 48
Figure 29: AFO Digital Model Refinement Stages ......................................................................................... 49
Figure 30: Complete field of view from a single scan .................................................................................... 50
Figure 31: Impact strength of RP materials (IZOD Notched). SLA series in orange, FDM series in purple, SLA
series in green. ............................................................................................................................................... 54
Figure 32: Stress vs strain of Duraform EX in three build orientations .......................................................... 56
Figure 33: Tensile destructive testing samples for Duraform EX in three orthogonal build orientations ...... 57
Figure 34: RP AFO Build Chamber Orientation .............................................................................................. 58
Figure 35: Custom RP SLS AFO ....................................................................................................................... 59
Figure 36: Polypropylene AFOs (A) Off‐The‐Shelf Posterior Leaf Spring (B) Flexible AFO (C) Semi‐Flexible
AFO ................................................................................................................................................................ 59
Figure 37: Trimline Comparison for Flexible & Semi‐Flexible Polypropylene AFOs ........................................ 60
Figure 38: Ankle Angle for A) Right & B) Left No AFO ................................................................................... 63
Figure 39: Ankle Moment A) No AFO; B) PP PLS; C) PP Flex .......................................................................... 64
Figure 40: Ankle Power A) No AFO; B) PP PLS; C) PP Flex .............................................................................. 65
viii
Figure 41: Left & Right Ankle Comparative Dorsi & Plantar Flexion Angle (Deg): ......................................... 66
Figure 42: Left & Right Comparative Ankle Dorsi & Plantar Moment (Nm/kg): ............................................ 66
Figure 43: Left & Right Comparative Ankle Power (W/kg): ........................................................................... 67
Figure 44: Recumbent Stationary Bike with Exercise Kit Attached ................................................................ 72
Figure 45: Bike System Complete Overview Mounted on Upright Stationary Bike ....................................... 74
Figure 46: Grip vs tendon force for multiple cylinder sizes conclude that a diameter of 38mm allows for the
greatest grip force and least tendon force required [59]. ............................................................................. 76
Figure 47: Variation for steering angle vs time on a 250 m track transitioning from a curve to a
straightaway [27] .......................................................................................................................................... 78
Figure 48: Early Pedal‐body strain gauge [27] ............................................................................................. 82
Figure 49: Piezoelectric transdeucer [27] ...................................................................................................... 82
Figure 50: fixed‐shaft strain gauge design [27] ............................................................................................. 82
Figure 51: A pedal from Penn State University to measure force and pedal orientation during cycling [27]82
Figure 52: Commercial stationary bikes & simulators ................................................................................... 89
Figure 53: Overview handlebar system CAD and physical implementation .................................................. 91
Figure 54: Schematic of handle system with major components and sensing of unidirectional of force ...... 91
Figure 55: Omega PX26 hydraulic pressure differential sensor ..................................................................... 93
Figure 56: Overall view of handle with detail on channel housing and handle cap ...................................... 94
Figure 57: Detail views of tube arrangement on front and back of handle ................................................... 95
Figure 58: Detail view of channel arrangement on handle body................................................................... 96
Figure 59: Handle 3 prototype single channel detail views ........................................................................... 97
Figure 60: Detail views of handle 4V1 prototype with multi‐channel tubing and detail of sensor housing
compartment ................................................................................................................................................. 99
Figure 61: CAD rendering and physical prototype handle 4V3 in application ............................................. 101
Figure 62: Overview pedal system ............................................................................................................... 102
Figure 63: Detail components view of pedal assembly ............................................................................... 103
ix
Figure 64: Application detail and pedal cross‐section ................................................................................. 104
Figure 65: Detail view of pedal interior assembly ....................................................................................... 106
Figure 66: Vibrating element and attachment locations inside pedal binding ............................................ 107
Figure 67: Schematic of SGAU strain gauge signal amplifier ...................................................................... 110
Figure 68: Overall view of power and signal boxes ..................................................................................... 111
Figure 69: Information communication diagram ........................................................................................ 112
Figure 70: VRehab main interface front panel ............................................................................................ 114
Figure 71: Loop and data logging controls .................................................................................................. 115
Figure 72: Handlebar display and controls .................................................................................................. 115
Figure 73: Pedal force display and controls ................................................................................................. 116
Figure 74: Pedal angle display ..................................................................................................................... 116
Figure 75: Velocity and RPM controls and display ...................................................................................... 117
Figure 76: Heart rate and vibration controls and display ............................................................................ 117
Figure 77: Minimum and maximum controls and display ........................................................................... 118
Figure 78: VR simulation menu ................................................................................................................... 119
Figure 79: VR Simulation during a Session .................................................................................................. 120
Figure 80: Testbed 1 to evaluate sensor with inline hydraulic chambers .................................................... 121
Figure 81: Testbed 2 to Evaluate Sensor with Adjacent Tube Arrangement ............................................... 122
Figure 83: Calibration schematic, hardware, and procedure ...................................................................... 125
Figure 82: Handle 4V3 calibration paddle ................................................................................................... 125
Figure 84: Mass vs Voltage Data for Testbed 1 for two different paddle thicknesses. Data has been
averaged for results from both chambers over 5 trials each. ...................................................................... 128
Figure 85: Mass vs Voltage Data for Testbed 2 for two different paddle thicknesses. Data has been
averaged for results from both chambers over 5 trials each. ...................................................................... 129
Figure 86: Concentrated loading on Testbed 1 simultaneously on both chambers ..................................... 130
Figure 87: Concentrated loading on Testbed 2 simultaneously on both chambers ..................................... 130
x
Figure 88: Mass loading location vs voltage response for thin paddle Testbed 1. Data has been averaged
for results from both chambers over 5 trials each. ...................................................................................... 131
Figure 89: Mass Loading location vs voltage response for thick paddle Testbed 1. Data has been averaged
for results from both chambers over 5 trials each. ...................................................................................... 131
Figure 90: Mass loading location vs voltage response for thin Paddle Testbed 2. Data has been averaged
for results from both chambers over 5 trials each. ...................................................................................... 132
Figure 91: Mass loading location vs voltage response for thick paddle Testbed 2. Data has been averaged
for results from both chambers over 5 trials each. ...................................................................................... 132
Figure 92: Handlebar forces vs pedal rpm ................................................................................................... 134
Figure 93: Handlebar forces close‐up comparison ...................................................................................... 134
Figure 94 A & B: Right Hand (A) and Left Hand (B) forces during steady pedaling motion for Trial 2 ........ 135
Figure 95: 0‐70% MCL for grasping during rest averaged for three trials ................................................... 136
Figure 96: Left Pedal (Blue) Right Pedal (Red) Loads during 5 Seconds of steady symmetrical pedaling ... 137
Figure 97: Normalized Curve for Left & Right Pedal Forces for 1 Rotation.................................................. 137
Figure 98: Error values for Testbed 1 for thin & thick paddles. ................................................................... 142
Figure 99: Error values for Testbed 2 for thin & thick paddles. ................................................................... 143
Figure 100: Position, velocity, and tilt sensing using 3 rotary string potentiometers ................................. 150
Figure 101: SLA material flexural properties range ..................................................................................... 161
Figure 102: FDM material flexural properties range ................................................................................... 161
Figure 103: SLS material flexural properties range ..................................................................................... 162
Figure 104: SLA material tensile properties range ...................................................................................... 162
Figure 105: FDM material tensile properties range..................................................................................... 163
Figure 106: SLS material tensile properties range ....................................................................................... 163
Figure 107: Recessed and elevated states of adjustable incline gait ramp ................................................. 167
Figure 108: Ramp Subassemblies ................................................................................................................ 170
Figure 109: Structural Walkway Frame Detail ............................................................................................ 171
xi
Figure 110: Gas Spring Detail ...................................................................................................................... 172
Figure 111: Gas Springs in Fully Compressed State between the cross‐beams ........................................... 172
Figure 112: Clearances for Expanded and Compressed Gas Springs ........................................................... 172
Figure 113: Reaction Normal Forces and Center of Mass ........................................................................... 173
Figure 114: Force Convention for Gas Springs ............................................................................................. 173
Figure 115: Net Force vs Inclination for Hinge Barrel .................................................................................. 174
Figure 116: Mechanical Safety Stop Raised & Recessed Configurations ..................................................... 175
xii
List of Tables
Table 1: Comparison between commercially available 3D scanners ............................................................. 21
Table 2: SLA advantages & disadvantages [34, 35]....................................................................................... 25
Table 3: FDM advantages & disadvantages [33‐35] ..................................................................................... 27
Table 4: SLS advantages & disadvantages [34, 35] ....................................................................................... 29
Table 5: Accuracy of points through digital processing ................................................................................. 51
Table 6: Material properties of thermoplastics currently found in orthotic devices ..................................... 52
Table 7: SLS RP AFO Temporal Parameters ................................................................................................... 69
Table 8: Relevant Patents as Prior Art ........................................................................................................... 84
Table 9: Comparison for Tubing Material Properties .................................................................................... 98
Table 10: Average % error for Testbed 1 load location ............................................................................... 141
Table 11: Average % error for Testbed 2 load location ............................................................................... 141
1.0 Introduction
1.1 Goal & Motivation
The enclosed work aims to validate application of rapid prototyping (RP) and 3D
scanning as processes to enhance the capabilities of biomedical devices for motor
rehabilitation applications. These technologies expand the opportunities for mass-
customization of devices and services for patient populations with greater functionality
and availability in a telemedicine environment [1, 2]. This also coincides with the trend
of increasing quantitative evidence-based medicine by design of intelligent devices
utilizing embedded sensing electronics in an RP medium.
Stroke is the leading cause of disability in the United States [3] and impaired walking
function is a prevalent deficit post-stroke. Of the 700,000+ incidences of stroke each year
in the US [4]. Of the survivors, 65% recover with some degree of impairment or gait
abnormalities. Immediately post-stroke only 37% of stroke survivors are able to walk and
of those patients with initial paralysis post-stroke only 10% regain functional
independence. Of stroke survivors who are not initially paralyzed 75% do regain their
ability to use their affected leg and walk independently. These walking outcomes post-
stroke, however, may overestimate recovery because they may only be concerned with
kinematics and not magnitude of comparable kinetics with a healthy population [5].
2
1.2 Thesis Organization
The enclosed document is organized in a project-based format. Background has been
detailed according to material relevant to overall thesis motivation, and each chapter
addresses Rapid Prototyping and 3D Scanning technologies in a specific context. Each
chapter documents prior art, background, design & process descriptions, testing, analysis,
and conclusions specific to each project under the larger context of the thesis motivation.
Pertinent information regarding collaborators and sponsors for each project has been
listed in their respective introductions.
The following work is organized to show application and validation of these technologies
as a process (Chapter 3.0) and a system (Chapter 4.0) aimed at improving the quality of
evaluation & treatment of patients undergoing physical therapy.
3
2.0 Background
2.1 Ankle-Foot Anatomy
The center of the ankle joint consists of three primary bones: the tibiotalar, fibulotalar,
distal tibio-fibular articulations. The ankle joint is a hinge which only permits flexion-
extension (dorsiflexion-plantar flexion) movement of the foot in the sagittal plane. Other
rotations about the foot include inversion and eversion, (inward and outward rotation),
and pronation & supination which occur at axis of rotation about the calcaneus [6, 7].
Figure 1: Ankle-Foot anatomical bone structure [7]
The talus bone is the bone most superior in the foot and is supported from below by the
calcaneus bone (also known as the heel bone). These two comprise the tarsal bones in the
foot. This group is also connected to navicular and cuboid bones laterally which help
stabilize the ankle during normal function. Top of talus the tibia and fibula rest along a
4
smooth surface contact from medial to lateral sides and expands towards the lateral side
allowing for the ankle to be moved in a wider range in plantarflexion direction [6].
Figure 2: Ankle-Foot joints of major functional significance [7]
2.2 Incline Gait
Daily ambulatory demands of many urban and natural terrains introduce sloped walking
that requires variations in the kinetic and kinematic function of the lower extremities
compared to level walking [8]. The manner in which the skeletal configuration and
posture change to accommodate the modified incline surface geometry and new center of
mass is especially significant in understanding adapted neuromuscular control schemes
and how best to treat deficits in patient populations [9, 10].
The general shape and temporal occurrence for moment & mechanical power in both
level and downhill gait are similar even if the GRF amplitudes and moments differ [11].
It has been previously studied by Prentice et al. that lower ramp angles1 do not greatly
1 Lower angles in the study were considered 3° & 6° inclines. This study consisted of 6 Subjects: 3 male, 3 female all of whom were right leg dominant.
5
affect the ankle, knee, and hip moments since they are close to level gait, but higher
inclinations require a modified pattern especially for joint angles during heel contact [8].
When moving from level to incline surface there was found to be a two stage gait
transition. The stage 1 initial response took place during the swing phase to account for
toe clearance, and stage 2 is preparation for foot contact with the incline sections of the
ramp. The greatest change in limb kinematics were found during the stage 1 swing phase
just prior to landing on the new surface [8]. Cadence has also been shown to generally
decrease for both ascent and descent in ramp gait despite larger GRF during heel strike
and elevated hip, knee or ankle power [11].
The average city stair riser height corresponds to roughly 30° incline, which is significant
to include when considering steep incline gait study. When compared with results for
level walking, characteristics transitions from horizontal change more so for descent
rather than ascent. For stair walking trials by Stacoff et al., the average level cadence of
10 subjects studied was 1.4 m/s but dropped to .72 m/s for ascent and .78 m/s for descent
along stairs matching a 19.8° incline. The subjects’ GRF peaks for level gait were 1.19 &
1.17 Body-Weight (BW), for ascent were 1.2 & 1.7 BW and for descent 1.4 & 2 BW
[12].
Kinematics of incline ascent exhibits increased dorsiflexion in the ankle during mid-
stance to match the incline surface and increased plantarflexion at toe off to provide
greater propulsive power. This modified ankle trajectory only resembles level gait during
the early swing phase, whilst knee flexion increases during both GRF peaks. Changes in
the GRF peaks during heel strike are more dramatic for ascent, and for toe-off during
descent [10]. Hip elevation and flexion differ somewhat between small inclines and level
6
gait. Increases in the early-phase forward pitch is less sensitive to ramp angle but occurs
further during higher ramp inclinations [8]. Movement adjustments for downhill occur
mostly at the knee during stance phase and ankle & hip during swing phase [11].
Figure 3: Comparison of angular kinematics and lower extremity joints during level and downhill (-19° gradient) walking averages for 12 subjects [11]
As seen in Figure 3, joint angles for the lower extremities exhibit modified patterns for
gait at incline descent. During swing the leg passes through the coronal plane later in the
gait phase and there is decreased hip flexion during heel strike compared to level gait
[11]. Greater knee flexion is needed throughout mid stance, but reaches a minimum
during heel strike at same instance as level gait.
7
GRF magnitudes differ greatly between level & incline gait. These magnitudes are
largely influenced by steepness but generally it has been understandably shown how
propulsive forces & hip moments increase for ascent and braking forces & knee moments
increase for descent [10, 12]. Compared to the peak forces of level gait walking as
roughly 1.1 & 1.3 times BW, Figure 4 from Kuster et al. shows increased loading during
heel strike (found as almost 30% higher in magnitude, occurring slightly earlier) and
smaller propulsive forces during toe off for gait on a descent.
Figure 4: Comparison of vertical and horizontal ground reaction forces from an embedded force plate during level and downhill (-19° gradient) gait averaged for 12 subjects [11]
8
It has been shown that mechanical power increases in all phases of slope walking except
down slope push-off which requires only 50% compared to level gait [11]. Few
differences in peak moment and power levels are shown between level and small inclines
like 3°, but already increase for 9° incline ascent especially exhibiting greater power at
the hip [13]. A study was conducted by Lay et al. with some results previously confirmed
by Kuster et al. that during down slope walking the mean and duration of power
absorption greatly increased at the knee by 30% compared to level walking for both
extension and activity level. During upslope, power increases primarily at the ankle and
hip by 25% as seen below in Figure 5 [11, 14].
Figure 5: Comparison of net joint moments for the lower extremities during level and downhill (-19% gradient) gait averaged for 12 subjects [11]
9
2.3 Current Corrective Rehabilitation Methods
The current section describes methods and devices used to evaluate and rehabilitate
patient populations with ambulatory deficits.
2.3.1 Gait Analysis
Currently in most gait labs, healthy and pathological human gait is studied for the
purpose of evaluating and diagnosing various clinical ailments. Figure 6 shows a sample
layout for the gait walkway at the Motion Analysis Laboratory (MAL, Spaulding
Rehabilitation Hospital, Boston, MA, USA) the pertinent kinetic data are collected via
two force plates embedded in the laboratory floor which measure ground reaction forces
upon heel strike contact by the patient/subject. Simultaneously, a motion capture system
tracks reflective markers located at the anatomical locations of interest to determine joint
kinematics. The kinetic and kinematic data are then synthesized into a computer model
that displays the real-time movements of the patient/subject. This model is then used to
aid clinicians in diagnosing musculoskeletal and/or neurological deficits with hope of
ameliorating their effects on ambulatory dynamics [15-18].
10
Figure 6: Gait Walkway in Motion Analysis Laboratory, Spaulding Hospital, Boston, MA. A)Vicon motion capture system, B) Force pads for recording ground reaction forces, C) Instrumented level walkway, D) Practitioner preparation area
The procedure to record kinetic & kinematic characteristics consists of attachment of
retro-reflective markers on key anatomical joint positions of the pelvis and lower
extremities, and ambulating along the walkway registering one heel strike per foot per
force platform. Trials are discarded if foot contact with the force platform was
incomplete, straddled with the surround walkway, or if visible stride alterations were
made to target the platform. It is important that the patient does not alter their gait pattern,
cadence, or force distribution in order to target the plates. This necessitates that the force
plates are as invisible as possible in the gait walkway. Also during gait trials patients
experience pauses up to 20-30 seconds between each pass of a trial, which necessitates a
stable waiting area at either.
11
The plates are positioned to record one step per plate per foot during a gait cycle. The
offset of the plates along the walking direction is equal to the average stride length for
patients studied in this laboratory which is 23.48”, (59.6cm) center to center.
Electromyography Data Acquisition
To track physiological activity of the legs, electrodes may be attached to the exterior
surface of key muscle groups. During rest and contraction of each gait cycle the EMG
data is matched in real-time with the inverse kinematics and center of pressure (CoP) data
from the force plates.
The EMG sensor cable bundle from the patient is held by a carriage along an overhead
track. As the patient moves between the end points the cables remain behind and above
the patient’s transverse plane. These do not interfere with the line of sight of the Vicon
system.
Vicon Motion Capture System
Figure 7: Reflective marker locations on lower extremities
Each of the cameras of the Vicon system emit strobed infra-red light, which when
reflected gives a grayscale view of each marker in 3D space. The co-ordinate of each
marker is then calculated within the camera from triangulation of the markers and
12
forwarded to a central PC. This PC receives co-ordinates from all the cameras and
automatically tracks the markers to establish 3D trajectories using inverse kinematics
[15-18].
Figure 8: Gait analysis using infra-red motion capture for joint kinematic and force plates for ground reaction forces[15]
This type of system can susceptible to occlusion problems for the markers and for
acceptable data to be gathered, line of sight cannot be blocked between the cameras and
the markers. Force plate, EMG and digital video data are combined to create a complete
kinetic & kinematic model of the subject walking. The green lines in the model above
move representative of the spheres between lower extremity joints.
13
2.3.2 Orthotic Devices
Depending on the severity of stroke and loss of neuromuscular control, the resulting gait
abnormalities are currently corrected by the subject being fitted with an Ankle-Foot
Orthosis (AFO) [7]. AFOs are intended to help stabilize the ankle-foot complex in
subjects with limited dorsiflexion, as in the case of drop foot [6].
The subject uses this orthosis to ambulate daily, so it is essential that its shape maintains
a high level of comfort whilst its material properties provide the stiffness and support
based on the subject’s needs. But AFOs are not created to fit specific subject anatomy.
Size ranges are built to fit an anthropomorphic range of ankle-foot anatomy
approximately, and are less likely to fit a particular subject comfortably. An AFO for
drop foot should be able to provide toe dorsiflexion during the swing phase,
medial/lateral ankle stability during stance, and some push-off stimulation during the late
stance phase for weak plantar flexors. The standard posterior leaf spring orthosis is one
type whose rigid structure prevents excessive drop foot in the swing phase [19, 20]. This
restriction of motion impedes plantar flexion and assists with dorsiflexion. Since patients
with drop foot have weak dorsiflexor muscles helping these muscles function has a
valuable impact on correcting their abnormal gait patterns [6].
Most orthoses are designed as a balance parallel force system, similar to a first-class lever
[21]. Figure 9-Figure 11 below are examples of Ankle-Foot-Orthoses of varying shape,
material, and targeted ambulatory treatment. Photos are courtesy of Robert Drillio, IAM
Orthotics & Prosthetics, Inc of Wellesley, MA, USA.
14
Figure 9: Bi-layer instep pediatric AFO with shell material removed to accommodate bony protuberances held in silicone
Figure 10: Jointed pediatric AFO with foot insert for patient with high tone in ankle-foot complex. Inner boot is comprised of modified polyethylene.
Figure 11: Rigid pediatric AFO with plaster zoat, peelite, and alliplast inner linings
Each foam material is vacuum-formed into the polypropylene shell and trimmed for a
smooth transition so a wearer’s bony prominences are well padded without skin
breakdown from excessive moisture and friction.
15
Figure 12: Articulated Crouch Walker AFO for controlled dorsiflexion
For patients who have limited control over their quadriceps during gait, the AFO in
Figure 12 above has a built-in mechanical stop for limited dorsiflexion. A different
articulation of this AFO can also contain an elastic element and is particularly well-suited
to upslope incline walking. The spring elements can supplement the weaker biarticular
muscles during ramp accent to balance out the co-activation of antagonistic muscles [14].
For patients with neuromuscular or neuromotor dysfunction the AFO can substitute for
inadequate muscle function during key phases of the gait cycle for stability and cadence
control [21, 22].
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17
It is important to note that since the pedals are connected through the crank, deficits or
impairments of the plegic leg may be overcome by higher forces from the nonplegic leg,
disguising some of the negative work from resistive forces. This highlights the
importance of measuring pedal forces separately for hemiplegic patients to isolate these
forces.
Normative data for pedal angle and pedal force components are listed below in Figure 14
as a function of crank angle [27]Error! Reference source not found.. Positive forces
indicate compressive loads and negative forces indicates tensile loads.
Figure 14: Average normal and tangential components of pedal loading recorded during cycling at 350W, 90 rpm (n = 17 riders). Crank angle 0 & 360 corresponds to Top Dead Center [27]
18
Pedaling exercise has also been shown to stabilize trunk rotation and sway despite
postural abnormalities as a result partially because of the continuous smooth, constrained
trajectory of the feet.
During training however, it is vitally important to balance the amount of exertion with
muscle and trunk co-ordination so as to prevent reinforcing poor cycling form. This is
supported by studies showing exercise with no range of motion constraints is of greater
benefit than higher exertion with poor form and greater negative work [23].
2.4 Freeform Surface Capture Using 3D Scanning
3D scanning devices digitize freeform surfaces by capturing discrete co-ordinates. In
medical modeling they are used to re-create the form of an anatomically correct digital
model first and then a physical prototype / model that fits the anatomy of the human body
part. Such models have had successful implementation in preoperative planning, implant
design/fabrication, facial prosthetics post-surgery and teaching/concept communication to
patients or medical students [28-33]. These devices may be divided into two categories:
contact and non-contact.
Contact devices physically touch the surface and register the location by some sort of
deflection at the end effecter via electronic switch. Contacting touch-probes are often
very accurate over a wide measurement volume, and some instruments in this class are
among the most affordable devices available. There are contact digitizers that are
positioned manually to yield a single measurement at a time, or may be scanned across a
surface to produce a series of measurements. Contact instruments are often in the form of
19
an articulated arm that allows for multiple degrees of freedom of movement. The position
of each section of the arm is determined by encoders, glass scales, or in the case of the
more inexpensive devices, by potentiometers mounted in each joint.
Non-contact scanners are able to capture surface geometry without contacting it.
Discussion regarding the enclosed work will be limited to applications of non-contact
digital scanning.
3D Laser scanning:
3D laser scanners emit a laser beam normal to the surface to be scanned. The light
reflected back from the surface is captured as a 2D projection by a Charged-Couple
Device (CCD) camera and a point cloud is created using triangulation between the two
cameras and the laser emitter. Laser scanners have relatively high accuracy and speed
varying on the size of the target object to be scanned.
20
Figure 15: Konica Minolta Vivid 910 Laser scanner
Regarding safety, most commercial lasers used for scanning are rated well below any
harmful threshold for eye damage, but reflections on curved surfaces and other
inadvertent events can result in a potentially harmful focused beam [33]. Laser scanners
are unable to capture color or texture information without an additional image to wrap
around the digital surface.
Projected –Light Based Stereoscopic Scanning:
3D photogrammetric scanners use images captured from different points of view to
reconstruct a surface. Images are taken from at least two different known locations in
order to triangulate and measure “lines of sight” for each targeted surface. Given the
camera locations and orientations, lines are mathematically triangulated to produce 3D
coordinates of each unobscured point in both pictures necessary to reproduce an adequate
point cloud for shape and size reproduction. Thus, the remote sensing of a 3D object can
21
be completed simply and relatively quickly because photogrammetric systems can
measure multiple points at a time. However, accuracy over increasing distances can be
poor with some systems and is dependent upon the resolution of the camera and other
hardware parameters.
Table 1: Comparison between commercially available 3D scanners
22
2.5 Rapid Prototyping Techniques
An object with complex freeform 3D contours can be very challenging and very costly to
prototype & manufacture with traditional fabrication methods. Rapid Prototyping (RP,
but also known as “Layered Fabrication”, “Additive Fabrication”, or “Layered
Manufacturing”) is a fabrication methodology which opens possibilities to readily
fabricate these previously impossible features in a fast, accurate, and cost-effective way.
Traditional machining practices like milling and turning remove waste material until only
the part features remain. RP fabricates a three-dimensional object from the base up by
adding thin consecutive cross-sectional profiles of the object which bind together for a
complete 3D shape. Although there are many different fabrication materials, machines,
and procedures worldwide, the natures of these technologies remain similar.
The unique capabilities of RP have benefitted the engineering design process in reduced
development time & cost, greater variety in a family designs, and prototypes more
accurate to functional testing of the final device [32-36]. The first RP machines began
with 3D Systems in 1986, but the technology and industry have already made significant
strides in development in a relatively young life [35].
The normally has large time periods between design iterations for form and fit evaluation
can be significantly reduced with RP [34, 37, 38]. The high priorities of ergonomic
comfort & functionality in the medical device field were successfully met by utilizing RP
for design iterations in the enclosed work (see sections 3.0 and 4.0 for further details).
Although there are many types of RP and new processes are frequently being developed,
23
the following discussion will focus only on three major types directly pertinent to the
medical device field.
2.5.1 Liquid Based: Stereolithography
The sterolithography (SLA) process uses a laser beam to sequentially cure cross sectional
slices in a liquid photopolymer resin to create the 3D contours of the build object (Figure
16). The area of photopolymer that is hit by the laser beam2 partially cures into a
continuous thin sheet which is parallel with the X-Y plane. The platform upon which this
sheet sits is then lowered by one layer’s thickness (resolution capable on the order of
.05mm in the Z-axis) and the laser traces a new cross section on top of the first. Most
lasers are static in the machine and operate in the UV light wavelengths, with the beam
continuously redirected by mirrors for profile path. The standard laser path for building is
seen in Figure 17. Adjacent sheets bind together and continue to be built one on top of
another to create the final three-dimensional object. For any overhanging features in the
part a support lattice framework is built with each layer to stabilize the part geometry and
isolate the part surface from the build platform [33-35].
2 3D systems SLA machines for example have used Helium-Cadmium Lasers of wavelength 325 nm or solid-state Nd:YVO4 lasers of wavelength 355 nm 35. Chua, A.K., Leong, K.F., Lim, C.S., Rapid Prototyping Principles and Applications. 2005, Hackensack: World Scientific Publishing Co. 402.
24
Figure 16: Stereolithography build process [34]
Figure 17: Bordering, hatching, and filling for one square [33]
After the build process has been completed, some post processing is required. The
support lattice needs to be manually removed and the contact surfaces manually cleaned.
Isopropanol is a common chemical to assisst cleaning. After cleaning, the part must be
transferred to a UV oven to finish curing the resin. Until the part is removed from the UV
oven it is recommended to avoid direct contact since the uncured resin can cause
irritation to exposed skin.
25
Table 2: SLA advantages & disadvantages [34, 35]
Main Advantages: Main Disadvantages:
Excellent Surface Finish Degradation from Prolonged UV Exposure
High Strength Material Properties Post-Processing Requires HAZMAT
Availability of Transparent Materials Post-Curing UV Process Required
High Build Speed Limited Biocompatability for Prolonged Contact
Low, Predictable Shrinkage factors for resins3
2.5.2 Solid-Based: Fused Deposition Modeling
Fused Deposition Modeling (FDM) creates layers by extruding beads of heated
thermoplastic which bond as they contact each other and cool, as seen in Figure 18. FDM
can utilize many compositions of plastic; the most common being ABS, Polycarbonate,
or a combination.
Figure 18: Fused Deposition Modeling Process [34]
3 Most resins experience less than .1% shrinkage during build process, and dimensional tolerances are aided by consistent predictions for compensation 34. Grimm, T., User's Guide to Rapid Prototyping. 2004, Dearborn: Society of Manufacturing Engineers. 403.
26
The build chamber is an open space, with no surrounding material but heated air to
maintain a temperature just below the material’s melting point. Within the heated
environment when one layer of liquid plastic from the extrusion head contacts the layer
beneath it they will harden together as the two layers bind. A sample extrusion profile is
shown in Figure 19 below.
Figure 19: Fused deposition modeling contour and raster path for circular cross-section [33]
This process also utilizes a support structure, which is made of a different material than
the part body but is extruded from a neighboring head. Build and support material is feed
in like spools, and after the extruder has completed the cross-section in the X-Y plane,
the platform drops one layer thickness for the next profile. The Z-height layer thickness
ranges from .15mm to .35 mm from a wire filament typically 1.15mm in diameter [33-
35]. The high viscosity of the plastic limits the deposition rate, and resulting build speed
since the entire cross section must be filled with material. Post-processing for FDM
requires removing the support material, which is readily broken away or washed off
without requiring harmful chemicals.
27
Table 3: FDM advantages & disadvantages [33-35]
Main Advantages: Main Disadvantages: Extruded Material is Identical to Functional Thermoplastic Restricted Accuracy
Minimal Waste of build Material Restricted Build Rate
Ease & Simplicity of Post-Processing Unpredictable Shrinkage4
Ease of Material Change in Build Delamination Rate Allows Only 85% Material Properties Best Typically5
2.5.3 Powder-Based: Selective Laser Sintering
Selective Laser Sintering (SLS) uses a heat-generating laser beam (CO2) to sinter
consecutive layers of thermoplastic powder together into a complete object (Figure 20).
For each cross-section, precision rollers deposit a thin layer of powder on the top of the
build chamber. When the laser is directed to the profile it heats the particles beyond their
melting point and they fuse together into a solid mass. The narrow beam causes only
particles directly in front to reach the sintering point and although adjacent layers get
heated they do not melt and instead serve as continuous support. The platform descends
one layer thickness (range of .076mm) and traces the next profile (X-Y plane resolution
of 0.178 mm for feature edges). The build chamber is filled with inert Nitrogen gas to
maintain a consistent heat and laser strength until the part is complete. [33-35]
4 Even in a heated build chamber, a new filament contacting with the layer beneath is an abrupt cooling and introduces thermal stresses & distortions 5 See section 3.4.4 for more details on delamination.
28
Figure 20: Selective Laser Sintering Process [35]
For as many hours as it takes to build a part, it is required to cool down the chamber
before the part(s) can be freed from the powder and cleaned. The particles neighboring
the part walls stick slightly to the finished part and as part of the post-processing will
need to be blown away with compressed air. Materials have a common, quantified
shrinkage of 3-4%, which increases the tendency for parts to curl, bow, or warp if they
are improperly stored before cooling completely [34].
29
This process has been utilized for thermoplastics, composites, ceramics, and various
metals. For plastics it is commonly some derivative of nylon, and for metal is a
combination of titanium and stainless steel.
The unsintered powder from a build cannot all be re-used for following parts. After
remaining in a prolonged state of elevated temperature it will not bind as predictably as
before. This necessitates using at least 40% virgin (not previously heated) material for
every build platform. The remaining powder from previous build cycles is considered
scrap and disposed.
Table 4: SLS advantages & disadvantages [34, 35]
Main Advantages: Main Disadvantages: No Support Structure Required
Almost Half Virgin Material Required per Platform
Materials Available for High Flexibility High Startup Power Consumption
Biocompatible Materials Available for Short Term Implantation
Cost-Effective Build Requires Filling an Entire Chamber
Post-Processing Phase Simple
No post-curing needed
Larger Available Build Envelopes
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have made it possible to acquire digital models of freeform surfaces like the superficial
contours of the human body. The combination of these two technologies can provide
patient-specific data input corresponding to anatomical features (3D scanning); as well as
a means of producing a readily-instrumented patient-specific form output (RP) with
electronic components already embedded [36]. Together the technologies are ideally
suited for the development of patient-specific medical appliances and devices such as
orthoses. This chapter details a novel process that combines 3D laser scanning with rapid
prototyping selective laser sintering (SLS) to create such patient-specific ankle-foot
orthoses (AFOs).
In fabricating the orthoses the aim was to match or exceed the effectiveness of a standard
orthosis in terms of supporting and controlling ankle mechanics while providing superior
comfort and fit by customizing the orthosis to the subject’s specific anatomy and needs.
When evaluating an AFO, fit and function are the important characteristics to consider.
Maintaining a high comfort level around the calf band and the shell around the leg are
especially important so that the fibular head sustains minimal or no pressure. Posterior
leaf orthoses have a particular trimline configuration which allows them to treat drop foot
well because of their rigidity. However patients who have severe swelling or edema,
unstable ankles, or other ankle-foot deformities cannot use generic posterior leaf orthotics
because the mass-produced fit is poor. Patients with multiple foot problems need a
customized orthosis that can be made available to them quickly for a low cost. It is this
specific need that this work is addressing.
A novel process was engineered to utilize patient-specific surface data of the patient
anatomy as a digital input, manipulate the surface data to an optimal form using
32
Computer Aided Design (CAD) software, and then download the digital output from the
CAD software to a rapid prototyping machine for rapid fabrication. This process unites
3D scanning technology with rapid prototyping whilst also emphasizing the unique
advantages of each to their full potential for unique custom orthoses with high-resolution
surfaces.
3.2 Medical Applications & Prior Art
Literature has suggested that mass-customization is already a feasible application for
wearable devices in the medical field because of the end-user’s high sensitivity to
ergonomic comfort [39, 40]. Research has been conducted using 3D scanning and RP, but
to date not as a complete and validated methodology.
A combination of 3D scanning and model manipulation has been suggested to produce
aesthetically correct facial prostheses [30]. By scanning the subject’s healthy ear and
mirroring the resulting surface it provides a guide for plastic reconstructive surgery.
Facial scanning has also been used for compression masks on post-burn hypertrophic scar
management [33]. A scan of the subject’s face would be taken and used to generate a
computer-numerically controlled (CNC) mill path for a foam positive (copy) of the face.
Thermoplastic can be vacuum-cast around this positive and cleaned to create a patient-
specific mask. Non-contact inspection of burns has also been studied using laser Doppler
imaging [41] to evaluate deep-dermal & superficial burns. 3D scanning has also been
evaluated successfully as an accurate quantifiable means of tracking physical changes as
a result of facial fat deposits resulting from HIV positive patients with ongoing
33
lipodystrophy syndrome [42]. RP has also been accepted as a pre-operative planning tool
[29, 43] for complex cranial and maxilo facial surgical models.
3D scanning and digitizing for the orthotics domain has been previously suggested as
both a quantifiable means of capturing surface data as well as defining corrective
biomechanical parameters [41, 44]. Milusheva et al [45] have conducted further testing
using the unique possibilities of RP to fabricate AFOs in one step with features normally
difficult to incorporate into a design like RP springs. However, these design possibilities
have not yet been completed with verifiable clinical trials. Faustini et al have conducted
bench top mechanical testing with passive-dynamic AFOs manufactured via rapid-
prototyping procedures using plastic-based SLS materials [46]. The geometry of the
rapid-prototyped AFOs was based on with point clouds obtained using Computed
Tomography (CT) imaging of carbon-fiber models of an existing AFO. This procedure
still requires an existing AFO rather than generating the surface model directly from an
individual’s anatomy. SLS with titanium-based metal powder has been used for tissue
scaffolds in cranial facial implants as well as the implants themselves [31]. Titanium-
based SLS powders have also been used in total hip arthroplasty procedures performed to
alleviate the symptoms of trauma or degeneration of the hip [33] and nylon-based SLS
has been used in tissue scaffolding for cranial facial implants [47, 48].
In many medical cases, fabrication output of 3D scan data has been CNC, whilst the input
for RP fabrication has been CT or MRI-based. Judging from prior research, the next
logical step for application in orthotics is to combine the advantages of RP technology
with 3D scanning to create a surface model directly from the subject and validate the
resulting rapid-prototyped AFO with clinical gait analysis.
34
3.3 Existing Custom AFO Process
Orthotic devices, and, in particular AFOs are currently designed to fit a range of patients.
But the standard models do not provide individualized comfort or support. Any personal
adjustments made to the standard orthosis are carried out in a qualitative time-intensive
manner, so both comfort and function can potentially suffer considerably if not created by
a skilled orthotist.
First a complete gait analysis of the patient is necessary to determine the nature of the
patient’s gait abnormality and how to select appropriative measures to correct it. Once
this has been characterized, the fitting and fabrication process can commence as
documented in Figure 22 below. This process can take up to 4 hours fabrication time per
unit for an experienced technician.
Figure 22: Existing process documentation for custom AFO evaluation, fitting, and fabrication
35
The ankle-foot complex of the patient (subject) is first positioned into the subtalar neutral
configuration to normalize their skeletal alignment with the flat, level floor surface. In
this configuration the leg has a skin-tight nylon stocking where the orthotist marks key
anatomical features like the calcaneous, 5th metatarsal head and tibia with ink (Figure
22A). These marking map out where and how to perform corrective modifications in a
later fabrication phase. The patient form is then captured by wrapping a casting sock to
create a positive of the leg (Figure 22B). Once the cast has set it is cut away along the
anterior contour, in line with the tibia. The open edge of the cast is filled and plaster is
poured into the leg cavity removing the cast once set and casting the leg in plaster to
produce a copy bust of the patient’s leg in subtalar neutral (Figure 22B, C). During
casting the original markings on the sock can slide along the surface up to ½” away,
introducing fabrication tolerances. The tolerances necessitate that the technician have
some fundamental anatomical and kinematic gait understanding to scrutinize the
locations of the markings in these cases.
The plaster bust form is then modified and manipulated (ground/sculpted) to implement
the corrective measured dictated by the gait analysis results. Depending on the subject, a
1/8” surface offset for the cuboid, 1st metatarsal, and 5th metatarsal can be marked6. The
1st & 5th metatarsal on either side are key for how tightly the foot will be constrained in
the orthosis. Starting at the heel, key surfaces are built outwards with plaster by
embedding staples offset surface markers (Figure 22D). Once the leg bust has been
6 For a more complete list of standard AFO bust modifications see APPENDIX A: Custom AFO Detailed Process
36
modified, pre-heated thermoplastic is vacuum formed around the plaster (Figure 22E)
After cooling the unwanted plastic is cut away, leaving an uneven ¼” deep gash in the
modified leg bust, and requiring edges on the AFO to be ground down & smoothed
(Figure 22F) The vertical surface of the removed AFO is loaded along the Achilles and
bent forward by the technician to qualitatively check for even splay displacement during
weight bearing.
The modified plaster bust (form) is stored temporarily. Should the need arise to
completely re-fabricate a patient’s AFO, the gash in the modified plaster bust must be
repaired before a new thermoforming operation can take place. Due to warehousing
considerations, most leg busts in clinics are not kept for more than typically 2 months, so
for each bi-annual patient refitting, the whole process must start from the beginning with
a new positioning of subtalar neutral. To determine the most effective ways to merge 3D
scanning and RP with the AFO fitting and fabrication process it was necessary to
categorize the existing methodology into discrete phases as seen schematically in Figure
23.
Figure 23: Existing process schematic for custom AFO evaluation, fitting, and fabrication
37
The subject positioning and form capture are the two steps of placing the ankle-foot
complex into subtalar neutral, marking anatomical features, and casting the leg. Form
manipulation consists of all surface modifications to the plaster bust. This includes
sanding, smoothing, sculpting, and adding material to create the form of the corrective
AFO. The fabrication stage includes all thermoforming, grinding, and smoothing
operations. The final application is for the patient to effectively ambulate with the AFO
whilst the physical plaster form is stored at the orthotist clinic.
There are great opportunities for further quantifying, tracking, streamlining, and
generally improving this process according to the following observations:
• The existing process is very time consuming due to repetitive manual labor and lack of automation
• There is no quantitative methodology to assess or track the surface geometry of the leg bust, modified, leg, or AFO
• During removal of the vacuum-formed thermoplastic shell the cutting operation damages the original surface of the plaster bust, compromising the original artifact
• Physical storage constraints of the orthopedic clinic limit shelf life to two-to three-months. After which the leg bust artifact is destroyed
• New fabrication of an existing AFO bust is confined to physical location of the original orthotist clinic.
• For additional fabrications of an existing AFO, it is necessary to repeat almost the entire process per patient.
The orthopedics evaluation process to correct gait has improved considerably with the
introduction of new technology, but the fitting of a custom AFO remains a laborious and
time-intensive process. The technology of the existing AFO fabrication process has not
changed significantly since the mid 20th century, leaving many opportunities for
improvements.
38
3.4 Digital Custom AFO Process
The steps of the new digital process follow the existing process with greater traceability
and more quantified operations by emphasizing actions in a digital environment. The
existing process for fitting a patient’s AFO focused on capturing and modifying the
physical form of the subject. The new process has a more detailed focus by capturing and
modifying the data which makes up the original form. The following section explains
each step of the new process and how it relates to the existing model.
Figure 24: Digital custom AFO process
Subject Positioning: Once gait analysis has been completed and the orthotist has
determined the appropriate corrective measures for the patient, the form of their ankle-
foot complex is prepared. Anatomical features are marked and the foot is positioned into
subtalar neutral.
Data Capture: The surfaces of the patient’s ankle-foot complex are digitized using a 3D
scanner. The raw surface data is stored immediately on site. Scans are taken as necessary
39
to cover the entire surface area of the desired appendage. See Section 3.4.1 for further
details.
Data Manipulation: The raw scans are prepared and cleaned. Extraneous data from
around the appendage is removed as well as spike anomalies. The surface scans are
merged into a single digital bust and cleaned to fill holes and apply smoothing
algorithms. Modifications to the surface geometry are also applied at this time which
mirror any physical sculpting operations normally carried out by an orthotist to expand or
contract the anatomical features. Finally an STL instruction file is prepared for rapid
prototyping. See Section 3.4.3 for further details.
Fabrication: The orthosis is fabricated by means of rapid prototyping. Any additional
electronic components are embedded at this stage. See Sections 2.5 & 3.4.4 for further
details.
Data Storage: The state of patient data at each digital phase is recorded, as well as the
final STL file from fabrication. This information is kept in a medical database for future
AFO replacements or design iterations.
Application: The physical AFO is fitted to the patient and assists them in daily
ambulation. See Section 3.4.5 for further details.
40
Embedded Components: For greater monitoring and traceability of a patient’s medical
state, electronic sensing and data transmission components may be embedded during the
RP fabrication stage as suggested by De Laurentis [36]. This allows for iterating design
and geometry changes as necessary based on one or a combination of patient feedback,
biomechanical analysis of the device and its wearer, and measurements taken by
embedded sensing elements. These iterations could mean modifying the thickness of the
material, the trim lines indicating the edges of the material, locations of the embedded
components, density of the material generated during the fabrication process, etc. The
sensory data could also be monitored remotely from a rehabilitation facility by medical
staff, expanding the effective range of a single facility by treating instrumented orthoses
as patient-specific “mobile gait labs”.
Telemedicine Implications:
The technology also extends the reach of orthotist practices by virtue of the telemedicine
capabilities of this digital design and fabrication platform. This will allow reaching
remote patients with high quality orthotics services that transcend geographic and socio-
economic borders that exist today for orthotist practices. The physical location of data
manipulation, fabrication, and data storage are no longer necessarily adjacent to the form
capture in the orthotist’s clinic because all of the AFO modeling stages may be
transmitted digitally.
The digital process model expands on traditional orthotic fitting, fabrication, and
treatment in the following fields:
41
• Orthotists’ skills and expertise remain as the foundation whilst expanding user group
• Greater opportunities for fabrication expansion. Distributed manufacturing networks
allow for instant replacement for patient regardless of geographical location
• Decreased lead time because of digital pre-set operations and automated fabrication
• Greater opportunities for quantitative data analysis of AFO & patient. Surface map
allows for assessment and tracking of patient features throughout treatment.
• Digital record of each patient allows for anticipation of iterative design changes
3.4.1 3D Scanning of Superficial Anatomical Contours
Scan quality of bare skin is greatly impacted by physical characteristics of the subject,
environmental conditions, and the capabilities of the hardware used. Hardware and
lighting conditions can readily be controlled with appropriate calibration, consistent even
lighting and a stable scanner mount; but the greatest variation remains with the subject.
The average skin tone and hue vary from one person to the next, as well as the variation
of these parameters within a patch of skin. These are characteristics common in medical
applications which make it fundamentally difficult for 3D scanners to accurately digitize
superficial geometry of live human subjects. Skin allows wavelengths of light and
radiation to pass through for perform vital functions like production of vitamin D [49].
Much of the light emitted from a 3D scanner will experience sub-surface scatter when
passing through the epidermal boundary and refract or be absorbed under the skin surface
which limits the number of data points registered and generates errors spikes. For high-
accuracy laser scanners, the skin deformation from a single heartbeat is already greater
than their sensitivity in many cases. For thinner anatomy like the ear lobe these effects
from the circulatory system are even more prevalent and can induce small, but
42
uncontrollable scan deviations. Optical scanners also have difficulty capturing sharp
edges like individual hair follicles which scatter light in random directions away from the
receiver, making it impossible to accurately triangulate the point distance [33].
Challenges for scanning skin are summarized below:
• Skin Semi-Transparency • Variation in Skin Tone • Skin Reflectivity • Motion (Conscious & Unconscious) • Hair Follicles • Appendage Position & Orientation for Scan
The scans in Figure 25 below highlight some of the errors which can be problematic for
digitizing subjects. These were captured using a projected light stereoscopic scanner
(Genex Facecam, Technest, Inc., Bethesda, USA ) and have not been smoothed or
cleaned from post-processing, save removing extraneous point cloud data surrounding the
anatomical features of interest. Large surface patches of missing data can result from
excessive specular reflection [41], Even slight motion can cause anomalies as spikes in
the mesh, and hair follicles, and certain tones can be more challenging to record.
43
Figure 25: Examples of anomalies and inconsistencies with scanning skin for faces and right arm
Kovacs et al. have examined 3D scanning of the human face with a Konica Minolta Vivid
9i (Konica Minolta, Ramsey, USA) laser scanner and the deviations from shell vertex
points. In almost half of the measurements taken, deviations of 2mm resulted from
motion artifacts which indicate that it is best to minimize examination time and avoiding
repositioning of the subject [50]. Subjects during the experiment could keep a roughly
steady ‘freeze’ position for 10-15 seconds without considerable effort, but this window
can decrease considerably with patients who experience spasticity, severe pronation, or
other impairments as a result of stroke [4]. For continuous laser scanning systems (for
example the polhemus FastSCAN cobra) the time needed for even a small appendage like
the hand can take up to 8 minutes [51].
44
Automatic rotary tables have been examined for repositioning a subject for multiple scans
with a single scanner. Although this method is very effective for small objects with high
stability and low inertia like bone samples or anthropological specimens, a rotary system
would be less on a human because of the large motion and inconsistent sway experienced
as a result of the acceleration and deceleration from turning [50]. Scanning has also been
conducted with identical scanner hardware for subjects seated on a swivel chair with
good results [42]. Although it is important to note that significant scan data did not
overlap from one mesh to the next since the target areas were limited to the buccal fat
pads of left & right cheeks.
A robust scanning methodology was necessary to ‘normalize’ the surface and minimize
the variation in scan data. An opaque white nylon casting sock can stretch onto the
appendage and almost completely remove all variations is skin tone, whilst decreases
specular reflection and constraining the flesh. Potential problems from hair are thus also
eliminated without having to shave the appendage. When stretched, the stocking adds a
thickness of .25-65 mm to the skin surface.
Figure 26: Visual difference in scan quality for bare skin and nylon covered surfaces
45
The difference in surface scan quality between the covered and bare skin surfaces
highlights the practical importance of covering and normalizing exterior anatomical
surfaces whenever possible.
3.4.2 Genex Facecam 3D Scanner
This work was completed by using the Genex Facecam 3D scanner (Technest Inc.,
Bethesda, MD, USA). This scanner captures three images (two for surface shape, one for
color) with a 640x480 resolution field of view. During a scan, a pattern of colored light
is projected onto the target surface. The reflected light from this pattern is captured by
camera lenses at two 6 Mega-Pixel cameras at different locations, which will later
reconstruct the shape digitally. In order to get the most accurate data possible from the
3D scans a procedure was generated for scanning a subject’s ankle and foot. The design
required data from below the knee and to the posterior of the leg and also the ventral side
of the foot. The camera locations for scans are dictated by its range and field of view,
which directly impact the quality of the data. Although the resolution in the Z axis has
been factory calibrated as .5mm, it actually depends on the precision of the images from
the two views captured. Processing of the scan images computes values for the Z distance
from triangulation between the two images and does not depend on just the image
resolution. The images are combined into a point cloud using a proprietary algorithm for
stereo pattern matching (Geometry Systems, Inc., San Ramon, CA, USA).
46
The projected pattern is designed to help the camera to find better match, there are is
ongoing development using simple random patterns as well [33]. See section 3.4.3Error!
Reference source not found. for more details.
Scan Samples: Scan quality from projected-light 3D scanners can be sensitive to color tone and specular
reflection of a scan surface. Samples are shown below in Figure 27 for variations in
color, specular reflection, and angle of reflection based on scan object cross-section.
Scans were taken against a black matte background with leading edges 70 cm away from
the central lens.
The scanner was oriented for the cylinders perpendicular to the diameter. The square rods
were oriented with one edge directed at the scanner. The matte samples were evenly
coated with Krylon Dulling Spray 1310 (Krylon Products Group, Cleveland, OH, USA).
Glossy samples were evenly coated with Krylon UV-Resistant Clear Acrylic Gloss
Coating. The matte samples have higher diffuse reflections, and the glossy samples have
higher specular reflection based on the refractive index of each coating.
47
Glossy Cylinder Matte Cylinder
Glossy Rectangle Matte Rectangle
Figure 27: Matte & glossy sample scans of square and cylindrical cross-section
Under all conditions, white surfaces have the best scan quality for even surfaces. The
black sections are unable to reflect sufficient light and have the largest irregularities and
spikes. The high-gloss edges are difficult to register because they scatter light randomly
and appear as holes. In agreement with Li et al., circumference measurements of the
unmerged cylindrical cross-sections have the highest standard deviation compared to
length & breadth measures with the rectangular samples [51].
48
3.4.3 Digital Modification & Post-Processing
The following section contains all digital operations on the scans to clean and post-
process them before preparing the STL build file for fabrication via RP. All digital
operations were completed using GSI Studio (Geometry Systems Inc, San Ramon, CA,
USA).
Figure 28: Digital processes flow diagram for point cloud refinement
Preliminary Import: The image pairs from stereo photogrammetry are calculated as
point clouds by triangulating the patterns of scattered light across the 3D scanned surface.
Extraneous data is trimmed away from the edges of the AFO surface.
Processing: Scan anomalies and poor-fitting contours are removed by local curvature
maximum comparison and Gaussian hole-filling algorithms for each individual point
cloud. The clean point clouds are then merged into a single point cloud and a surface
mesh is fitted.
Inspection & Analysis: During each cleaning procedure it is important to evaluate the
continuity of the AFO’s curvature plot to detect local irregularities. The surface mesh
should ideally be a continuous smooth surface.
49
Surfacing: A parameterized surface is fitted to the mesh in preparation for functioning as
a CAD equation-driven feature reference. Once in CAD the surface may be referenced to
offset features, thicken surfaces, create cavities, or extrude features.
Figure 29: AFO Digital Model Refinement Stages
A: Point Cloud Raw 1 B: Point Cloud Raw 2 C: Scans Combined into single mesh D: Mesh decimated to reduce point and file size E: Surface parameterization for mesh F: Complete parameterized surface G: Curvature map of AFO surface
50
Figure 30: Complete field of view from a single scan
During a scan, data is captured which is relevant to the patient anatomy, as well as
extraneous data from the environment and the orthotist’s hands which must be removed.
By creating a large contrast in color between the patient’s anatomy and all other points
the unwanted data may be removed according to range of hue & saturation for the voxel.
The white balance from the patient’s sock-covered appendage has a high contrast with
the orthotist because of their blue gloves. Any surfaces covered by the blue gloves cannot
be registered from a scan, but may be added from a separate mesh captured when the
practitioner’s hands have moved to a different location on the patient’s ankle.
Deviation of Points over Varying Distances from Anatomical Landmarks for Scan Accuracy after Digital Modeling 10 pairs of points were marked for each of the three ankle-foot regions. For each region,
5 pairs were marked with 40mm separation and 5 pairs were marked with 120mm
separation from an orthogonal coordinate system centered at the base of the calcaneous
and parallel with the tibia and 1st ray. Deviation of each point between multiple scans was
51
measured physically and digitally to track tolerance and error. Deviations were averaged
between the number of overlapping scans from the modified plaster bust of the subject’s
ankle-foot complex as described in section 3.4. Scans were taken from this as a static
surface with consistent tone & texture and evaluated for accuracy similar to experiments
conducted for the hand by Li et al [51].
Table 5: Accuracy of points through digital processing
These deviations are comparative to previous work of facial scanning using similar
hardware who have found average deviations of 1.32mm with standard dev 5.67mm [50].
It is also comparative for deviations from 3D scanning in an experimental group of 46
subjects [51].
Results for 3D scanner accuracy and precision, and best practices determined for
positioning, capturing, and processing individual co-incided with best practices and
results observed in the 3D scanning field [42, 50, 51].
52
3.4.4 Material Selection
For medical applications in orthotics, although it is important to primarily consider
material properties, it is impossible to separate the material from the process and so
performance characteristics of both must be discussed concurrently since the process
settings will significantly change the material properties expressed in a part [33, 48].
Table 6 below lists the mechanical properties of currently employed thermoplastics to
fabricate different components of AFOs [21] The mechanical and thermal properties
below are the design goals for selecting an appropriate RP alternative.
Table 6: Material properties of thermoplastics currently found in orthotic devices
See Appendix B for more documentation and graphical comparisons of material
properties for the three ranges of RP materials discussed below. It is important to note
that the Z-build orientation can change material properties considerably (as seen below in
Figure 32), and in most cases material properties for RP are listed without reference to
the orientation of build for the testing sample [52, 53].
53
Stability:
SLA parts are susceptible to shrinkage and distortion even after post-processing. Heat,
moisture, and contact with chemical agents will affect the color, shape, and integrity of
the material. Moisture and heat causes the part to soften and creep, while continuous
exposure to UV light will darken the color and increase the opacity of the resin. These
wavelengths already cure the resin in the build chamber, and under further UV exposure
with embrittle the parts. Material properties for FDM do not change from time or
environmental factors and remain consistently resistant to heat and chemical exposure to
alcohol, acids, and bases. SLS parts also retain high dimensional stability once removed
from the build process. The nylon material series can withstand moisture, heat, and many
other chemicals without warping or swelling [33, 34].
Feature Definition:
The SLA feature creation capabilities are defined by the laser spot size (most laser
diameters are .25mm) with the highest level of detail possible. The smallest features for
an FDM cross-section are limited to twice the diameter of the extruded bead because it
will always trace an outline of each edge for the cross-sections. The strata from FDM are
more course than SLA or SLS and could have a potential impact on wearer comfort. SLS
lasers require a larger beam to generate sufficient heat and have typical features
generation of .64mm.
54
Thermal Properties:
SLA materials do not respond well to heat and have a low creep temperature compared to
other RP processes [35]. On the other hand, the thermoplastic materials used by both
FDM and SLS may be heated above the melting point and their features reformed to an
extent before the material re-cools and solidifies. All FDM-based ABS plastics are inert
and nontoxic developed from commercially available thermoplastics and waxes. Hence
the latter two processes offer orthotists a transition from polypropylene familiar to its
thermal reshaping capabilities [33].
Impact Strength:
The IZOD notched impact test (ASTM Standard D256) is common to compare relative
impact resistance of plastics and was used as a comparison for impact loading on RP
materials from the three processes discussed.
Figure 31: Impact strength of RP materials (IZOD Notched). SLA series in orange, FDM series in purple, SLA series in green.
55
SLA materials are the most brittle and possess the lowest resistance to impact of the three
processes. Most FDM materials are generally comparable to SLS with a few exceptions
specially designed for high-impact loading. This material property is significant for
durability during gait as well as blunt impact from daily routine. During stair & incline
ambulation the impact for heel strike can increase up to three compared to level gait
characteristics and should be considered for material thickness and trimline
considerations.
Flexural Properties:
SLA is generally more brittle than other RP methods presented here, but has specialized
ranges of materials which can almost imitate thermoplastics like polypropylene,
polyethylene, ABS. FDM plastics have excellent flexural properties but also have the
highest rate of de-lamination and if the build process is not carefully setup can separate
even if the material has not passed its yield point [53]. The two primary types of SLS
polyamides have the powders based on commercial nylon characteristics. Some
variations have increased strength and rigidity (Duraform GF, 3D Systems, Valencia,
USA) by adding glass beads to the material mix. For glass-filled SLS, the glass particles
embedded in the nylon-powder matrix increase the elastic modulus, but lower the tensile
strength and impact strength of the SLS nylon [33]. Refer to Appendix B for more
detailed graphical presentation of flexural properties.
Tensile Properties:
Since SLA materials are brittle, they experience almost no plastic deformation zone prior
to failure ultimate. They possess higher tensile strength but lower elastic modulus than
56
FDM and SLS. FDM users have reported that tensile testing of ABS plastics between 70-
80% of the strength of injection-molded ABS [34, 35]. This decrease is a result of the
delamination effect from consecutive layers of thermoplastic bonding. SLS materials
have good elastic moduli and yield stress comparable to many SLA and FDM materials.
Refer to Appendix B for more detailed graphical presentation of tensile properties.
Material properties of RP fabrication schemes are anisotropic in nature and so vary
depending on build orientation. Tensile destructive testing for SLS material samples of
Duraform EX was conducted for three build orientations as seen in Figure 32 below using
an Instron Tensile Tester (Instron, Shakopee, USA).
Figure 32: Stress vs strain of Duraform EX in three build orientations
Results above were averaged for five samples built in three orthogonal Z-axes. The yield
point for this material is listed as 37 MPa, but it is paramount to also consider the build
57
orientation since two of the three samples fail below this point. It is also worth noting the
difference in failure mode depending on orientation. Sample A acted more like a brittle
SLA material since it did not have a well-defined yield point with any plastic
deformation. A plastic deformation zone is also an important safety consideration to
minimize hazards to the wearer in the event that a failure mode occurred. Samples of
each build orientation failure are seen in Figure 33.
Figure 33: Tensile destructive testing samples for Duraform EX in three orthogonal build orientations
The part will always carry the highest mechanical properties when the Z-build axis is
normal to the cross-sectional build planes of greatest surface area. Sample B had the
greatest ‘necking’ and largest elastic deformation zone. Sample C was more prone to
failure at stress concentration zones, and sample A was the most brittle.
58
Considering the characteristics discussed above, SLS Duraform EX was chosen as the
primary material for fabricating and testing the RP orthoses.
3.4.5 SLS & Polypropylene Custom AFO Comparison
Following the process described in section 3.4 an SLS AFO of nylon 11 was fabricated
from based on scanned data from a sculpted plaster bust. The trimline configuration and
material thickness (3mm) were set to match the semi-flexible polypropylene AFO.
Following the discussion above for mechanical material properties and Z-axis, the build
orientation was set to maximize the tensile yield point by aligning the horizontal datum
along the Achilles as shown in Figure 34 below.
Figure 34: RP AFO Build Chamber Orientation
The AFO in Figure 35 was built in a P730 SLS system (EOS, Novi, MI, USA).
59
Figure 35: Custom RP SLS AFO
Following the process as described in section 3.3 two custom polypropylene AFOs were
fabricated using the conventional process.
Figure 36: Polypropylene AFOs (A) Off-The-Shelf Posterior Leaf Spring (B) Flexible AFO (C) Semi-Flexible AFO
AFO A is an off the shelf polypropylene posterior leaf spring orthosis and was sized from
nearest available fit. AFOs B & C were fabricated based on trimline contours to give
greater (flexible) freedom in dorsi & plantarflexion angle and less (semi-flexible)
freedom for range of motion.
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60
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61
3.5 Comparative Testing for AFO Gait Analysis
A range of AFOs were examined for comparative impact on ambulatory dynamics for
level gait analysis. Evaluations of a single healthy subject without any reported gait
impairments were conducted at Spaulding Rehabilitation Hospital, Boston, MA using a
motion capture system. A healthy subject was used as a control in order to examine
deviations from normal gait without an AFO compared to gait with an off-the shelf
posterior leaf spring AFO (Alimed, Dedham, MA, USA), two custom polypropylene
AFOs of varying flexibility, and a rapid-prototyped custom AFO fabricated from SLS
nylon 11 using 3D scans of the modified plaster bust.
3.5.1 Experimental Setup
For gait testing sneaker gait (no AFO) was compared against the standard
(polypropylene) AFO with off-the shelf trimlines, a flexible configuration of custom
AFO, and the rapid prototyped AFO made from SLS Nylon 11. The subject was a right-
foot dominant healthy adult with no previous ambulatory or cognitive deficits and wore
the AFOs on their right side. Four different conditions were tested during the gait
evaluations: 1) with sneakers and no AFO (No AFO); 2) with the standard polypropylene
posterior-leaf spring AFO (PP PLS); 3) with the flexible custom AFO (PP Flex), 4) and
with the custom RP AFO (SLS RP). Each of the different AFOs were fitted to the right
leg of the subject during the level walking trials.
To characterize the gait pattern of the subject reflective markers placed with on the
following specific anatomical landmarks of the subject’s pelvis, and knee, ankle and foot
62
of each leg: bilateral anterior superior iliac spines, posterior superior iliac spines, lateral
femoral condyles, lateral malleoli, second metatarsal heads, and the calcanei. Additional
markers were also rigidly attached to wands and placed over the mid-femur and mid-
shank. The subject was instructed to ambulate along a 20 foot walkway at their self-
selected comfortable speed for all of the walking trials. An 8-camera motion capture
system (Vicon 512, Vicon Peak, Oxford, UK) recorded (120Hz) the three-dimensional
trajectories of the reflective markers during the walking trials. Two force platforms
(AMTI OR6-7, AMTI, Watertown, MA) embedded in the walkway surface recorded
(120Hz) the three-dimensional ground reaction forces and moments during foot contacts
onto the platforms. Five walking trials with foot contacts of each foot onto the force
platforms were collected for each AFO condition.
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3.5.2 Experimental Data
RIGHT Lower Extremity Indicated in Green
Left Lower Extremity Indicated in Red
Right Ankle Angle:
Figure 38: Ankle Angle for A) Right & B) Left No AFO
64
Right Ankle Moment:
Figure 39: Ankle Moment A) No AFO; B) PP PLS; C) PP Flex
65
Right Ankle Power:
Figure 40: Ankle Power A) No AFO; B) PP PLS; C) PP Flex
66
SLS RP AFO: Sagittal Plane Kinetics & Kinematics
Left Lower Extremity Indicated in Red
RIGHT Lower Extremity Indicated in Green
Figure 41: Left & Right Ankle Comparative Dorsi & Plantar Flexion Angle (Deg):
Figure 42: Left & Right Comparative Ankle Dorsi & Plantar Moment (Nm/kg):
67
Figure 43: Left & Right Comparative Ankle Power (W/kg):
68
3.6 Analysis & Discussion
Range of motion is comparable between the right & left ankles as seen in Figure 38. Both
dorsi and plantarflexion angles are comparable with close standard deviations. Data from
each brace condition will be compared with characteristics of the right leg with No AFO.
Moments about the right ankle for No AFO matched magnitudes and temporal locations
with normal gait. For the PP PLS and PP Flex AFOs the shape of the moment curve
matched the No AFO condition for peak location, but magnitudes have decreased by 24%
and 18% respectively. During controlled dorsiflexion both AFOs exhibit a more shallow
increase in moment and smaller local peak during the first 20% of gait. The drop in ankle
moment is likely from the increased constraint around the joint, making it more
challenging to overcome the resistance of the material between the controlled
plantarflexion phase and powered plantarflexion phase. Standard deviations around peak
ankle moment were also considerably higher for both AFOs indicating a slightly greater
instability just prior to heel strike. The data indicates that the off-the-shelf PP AFO and
the custom PP AFO perform comparatively for ankle moment.
Power generated at the ankle was significantly reduced for both PP PLS (84%) and PP
Flex (57%) in Figure 40, but exhibits the same patterns as healthy gait. This is as
expected from the material resisting motion, which can also be a benefit to patients
requiring increased stability during powered plantarflexion. Both AFOs show a higher
standard deviation around peak power just prior to heel strike, again indicating an
inconsistency in gait patterns. This may be due to greater compliance of the
69
polypropylene material from which the standard AFO is made or a poorer fit of the AFO
around the foot and ankle of the subject compared to the custom PP Flex AFO.
Range of motion for the SLS AFO in Figure 41 exhibits comparable patterns and
magnitudes to normal gait, as well as symmetry between the left and right ankle.
Dorsiflexion angle does not appear to be reduced as significantly as the other AFO
conditions, although plantarflexion has decreased compared to Figure 38. The temporal
parameters for the rapid-prototyped AFO are listed below in Table 7. Cadence was
consistent between trials and comparable to gait with No AFO, indicating that this brace
condition did not significantly inhibit ambulation.
Table 7: SLS RP AFO Temporal Parameters
Moments generated between the right and left ankle differ in magnitude and shape
similarly to the other AFO brace conditions, although the SLS AFO does not decrease the
controlled dorsiflexion local maximum as significantly.
70
Amplitude of power generated in dorsi and plantarflexion is greater in the AFO ankle and
non-AFO ankle, and almost 33% more absorbed compared to No AFO. This is to
counteract the increased resistance from the material in dorsiflexion, which yields a
understandably greater peak in powered plantarflexion when the elastic material releases
energy. This attenuated peak power is likely due to the restricted plantarflexion of the
ankle during push off imposed by the AFOs
There is some evidence in specific phases of the gait cycle e.g. CP and CD, that the RP
AFO can stabilize the movements of the ankle better than the standard AFO by absorbing
greater power without impairing range of motion. Overall, when comparing the three
AFOs that they perform similarly in terms of controlling ankle kinematics and kinetics
during the gait cycle, with some small deviations according to material and trim line.
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3.7 Conclusions & Future Work
This technology is capable of increasing the numbers of patients serviced per year per
orthotist while reducing overall the orthosis fabrication cost and time. The platform
enables new tele-rehabilitation treatment structures with remote instrumented AFOs. For
example, strain sensors may be placed at key locations at the Achilles and calcaneous for
predicting and tracking the fatigue of the orthotic device and for estimating when the
orthotic device might be most likely to break and what the failure mode might be.
Despite differences between orthoses it can be noted that the change in ankle power is
still relatively small, and that increased material flexibility will help to improve
performance. The trimline selected for the SLS AFO matched a semi-flexible
configuration of the PP AFO and will need to be further investigated for differences
between not just material but edge contour as well. Measuring anatomical deviations over
an extended period with regular 3D scanning of a patient allows an orthotist to not only
design an AFO based on immediate parameters, but on whether the patient’s body has
been responding more favorably to a particular contour or surface feature. This
introduces digital evidence-based results to AFO design in addition to qualitative form
assessment.
Eventually these custom rehabilitation aids become pervasive smart mobility aids and
health maintenance devices with the important role in maintaining quality of life for
personal independent mobility.
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4.0 Modular Stationary Bicycle Kit for Evaluation
& Treatment of Patients Post-Stroke
Figure 44: Recumbent Stationary Bike with Exercise Kit Attached
This work was completed in collaboration with VRehab Inc, the University of Medicine
& Dentistry of New Jersey for testing, and with Mark Sivak for his assistance with the
software component of the project. Supplied bindings were also donated on behalf of
Flow, San Clemente, CA.
4.1 System Overview
A system was designed to simultaneously improve cardiovascular ability, neuromuscular
endurance, and fine motor control for patients post-stroke by training them in a safe
seated position on a stationary exercise bike. The training exercises are consistent with
specific preventative training principles for neural plasticity and task-specific training.
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The final goal of training patients with this system is to allow them to transfer the
improved endurance and motor functions to every-day mobility and interactions.
Several hardware and software elements were implemented to a stationary exercise bike
to monitor physiological parameters of patients post-stroke whilst immersing them in a
virtual simulation providing visual and haptic feedback. This system is modular &
adaptable enough to be attached to current commercially-available stationary bike
systems and interfaces with a personal computer for simulation and data acquisition
processes. Design iterations were completed by employing RP tools and processes for fit,
ergonomic evaluation, and concept selection.
The complete bike system includes the handle system, pedal system, and some additional
electronics to measure heart rate and perform data acquisition. The parameters monitored
by these systems are communicated to a practitioner’s interface screen and a virtual
environment which provides visual feedback on the rider’s progress. The signal gain of
these parameters can be adjusted by the practitioner to the patient’s range of motion,
strength, and physical endurance level.
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Figure 45: Bike System Complete Overview Mounted on Upright Stationary Bike
Signals are acquired and amplified from two
identical handlebar systems (A), two nearly
identical pedal systems (B), the heart rate
monitor system (C), and sends the signals to the practitioner interface (F). The data from
the sensing systems is sorted and streamlined into a User Datagram Protocol (UDP)
signal used to drive the virtual environment (G).
All components are tethered and powered by the power & signal boxes (D, E) with the
exception of the heart rate monitor which has wireless components.
A: Handlebar System B: Pedal System C: Heart Rate Monitor D: Signal Box E: Power Supply Box F: Practitioner Interface G: Virtual Environment
75
The handles have adjustable Velcro fasteners to fix to the range of current handlebar
diameters currently available, as well as rotate for a custom rider posture during
evaluation. The pedals systems are fitted with the standard threads for stationary exercise
bikes, and readily replace them via insertion to the crank arm.
4.2 Medical Applications & Prior Art
Research for Instrumented Handlebars & Grasping Biomechanics:
It has been found previously that maximum grip force is primarily a function of shaft
diameter [54-56]. Handle diameters in the 23mm-32mm range have exhibited primarily
lower forearm muscle activity during a power grasp, and a 38mm diameter has previously
been found to have the best efficiency if measured by ratio of grip force to EMG activity
[54] as detailed in Figure 46. Although the diameter for optimum power grasp may not
necessarily be the same diameter for optimal comfort [56]. In one study by Kong et al 24
participants evaluated handle diameter for maximum force and subjective comfort, where
finding indicated that although there was a discrete diameter for highest force (35mm for
females, 40mm for males) the diameter for greatest comfort was 19.7% of the user’s hand
length [57].
It is important to note that there is an uneven distribution in the phalange forces which
can vary roughly 10% between digits, but Kong et al has determined that these relate
more to handle shape than handle size when employing maximum gripping force [58].
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Grip vs Tendon Force for Multiple Cylinder Sizes
Figure 46: Grip vs tendon force for multiple cylinder sizes conclude that a diameter of 38mm allows for the greatest grip force and least tendon force required [59].
Current commercial handlebars for bicycles and stationary exercise bikes are in the range
of 32-42mm diameter, which includes any exterior finish like a deformable wrap (Cybex,
Medway, MA, USA; Easton, Van Nuys, CA, USA). These measurements support the
diameter ranges found previously as the optimal balance for a comfortable grasping
diameter which allows the user to exert the maximum force with smallest muscle fatigue.
Handlebars for a real or virtual bike are a control device regardless of medium, when
reviewing handle diameter for the applications in motor control, a 22mm handle diameter
was found best for fine manipulation by Cochran et al., but the hand configuration would
not necessarily be a power grasp to begin with [60]. This allows the smaller diameter
ranges to be discounted from consideration since turning a bike’s handlebars is not a fine
motor control activity.
Definitions of analytical measures for defining a grasp have been previously outlined by
Ctucosky et al [60]. When a particular object may be used in multiple applications and
functions, the grasp orientation and configuration can change considerably along with the
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maximum comfortable forces. It can be assumed that grasping forces are radially
symmetrical for a power grasp [61] but not necessarily for a push/pull action on a bicycle
handlebar; necessitating force sensing over several locations on the cylinder. This has
been studied by Chadwick et al using an alternative dynamometer design which included
a 6-piece hexagonal rod with 30mm diameter [61] and successfully measured up to 250 N
max for an adult male test subject.
Considering adult hand anthropometry, there are a range of comfortable grasp diameters
for reasonable force output. Examining power grasp of a group of 43 people between the
ages of 10-53 by Yakou et al yielded results that the diameter for maximum force is
almost equal to the diameter of maximum surface contact. Furthermore that optimum
grasping conditions occur when contact with all finger tips and full area of palm exists
[56]. Comfortable grasp diameter has been discussed as 30-40mm ideal for adult males,
with comfortable grasp diameter for females is roughly 10% smaller which supports this
when comparing male and female hand anthropometry [56]. In a study by Drury et al
cylinders of diameter 31-38mm had the least reduction in grip strength over a fatigue test
to support a load [55]. The fatigue exercise is this study is comparable to the power grasp
maintained during bicycle exercise. Another fatigue study has determined that a cylinder
38mm diameter as the most force efficient (whilst least fatiguing) handle diameter
according to EMG measurements [54]. Bao et al collected normative data for power
grasp and force estimation from 120 healthy subjects. Power grasp averages and standard
deviations were 470N, 76 and 294N, 67 for males and females respectively [62]. From
the comfort and force estimation data collected 9% Maximum Voluntary Contraction
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(MVC) can serve as a design constraint for average comfortable power grasp for a
healthy adult male of roughly 44.3N when using the handles as a virtual input device.
Greater push/pull forces use more of the shoulder and forearm muscles than just the hand,
so previous work was examined according to reaction forces for wheelchair locomotion.
Kulig et al have investigated such forces during power grasp forearm extension which
were measured from level comfortable wheelchair propulsion. The average & maximum
shoulder forces and their reactions were taken into account for hard turning motions [63]
and considered as the maximum combined push force7. A shoulder extension yielded a
peak reaction force of 51N in a vector 85° posterior to top dead center.
For steering within the virtual environment it is important to mimic the reactions from a
real bike closely to maintain the user immersion. However even for a consistent smooth
turn there is some oscillation in the handle trajectory (Figure 47Figure 47), which could
be visually disturbing if not set correctly in the simulation visuals. This necessitates an
artificial dead zone in the software for the handles to avoid sudden and erratic motions of
the virtual rider.
Figure 47: Variation for steering angle vs time on a 250 m track transitioning from a curve to a straightaway [27] 7 Especially since wheelchair power grasp has an ulnar deviation characteristic of recumbent bicycles.
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Even straight, level pedaling regular motion causes slight oscillations in the upper trunk
and handlebar trajectory. The pedaling movement transferred to the arms from the legs
induces roughly a 2.5° periodic sway [27] which must be accounted for to determine the
dead zone implemented in software which does not affect the data collection, only the
visual feedback of the simulation. However this does not have to include the counter-
steering effect8 (occurring during controlled turning of a real bicycle or motorcycle)
because the torque experienced prior to the turn is already small [64].
Previous work has been considered on instrumented force dynamometers when the
application surface is the exterior of a cylinder. From an evaluation by Komi at al (2007)
Tekscan and Flexiforce were not greatly affected by the curvature of their mounting so
could potentially be fixed around a shaft [65]. Komi also recommended using a compliant
layer of material between the thin film sensor and the load to even out point loads [65].
However it was also found that the thin film sensors do tend to underestimate the loading
for curvatures 8-51.7mm diameters which is problematic for the diameter ranges listed
above for a bicycle handlebar.
Research for Instrumented Exercise Pedals:
The cadence vs force relationship of bicycle pedaling has been extensively examined and
determined to be highly linear [23, 24, 66]. Sargeant et al studied power and forces
exerted over a range of crank velocities (23-171rpm) for 5 healthy subjects. At this
optimum velocity subjects attained power maximum average and SD of 840 W 153W
respectively [25]. Brown had similar experiments with workload range (45, 90, 135,
8 Counter-steering occurs when the rider turns the opposite direction of desired route before leaning into a turn 64. Fajans, J., Steering In Bicycles and Motorcycles. American Journal of Physics, 2000. 23(4): p. 6.
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180J) and varying speeds (25, 40, 55 rpm) for healthy vs hemiplegic subjects [23].
Rogers et al also studied hemiparetic patients and found that min & max normal forces
for compression & tension (400N, 50N respectively) [24].
Hoes et al had very early experiments to characterize the forces exerted during pedaling
with an instrumented ergometer. They determined that with increased power output, the
peak pressure increased, whereas with increased cadence, the peak pressure decreased.
The relative loading on the regions of the foot appear to change very little with the
exception of the first metatarsal and hallux regions as shown by Sanderson [67]. In the
latter, relative load increased significantly with increased power output. With the
distribution of pressure relatively consistent, peak forces always occur are when the pedal
is just in front of the top dead center of the crank. This is where the passive (hind) leg is
lifted partially by the active leg, which effect diminishes at higher cadence [68]
Sanderson et al studied that with increased power output, there was also a reduction in the
negative impulse from the passive leg. In both amateur and competitive riding groups as
the intensity of the rides increased, the riders in both groups generated less of a retarding
force with the hind leg on the upswing. This reflected the strategy of the rider to improve
the effective application of force by reducing the need for the recovery leg to be
overcome by the propulsive leg. This changes somewhat in the case of hemiplegic riders
as explained by Brown et al. With increased power, both the positive and negative work
increased in the healthy and plegic legs. However there was an overall net positive work
for the increased cadence and all 15 post-stroke plegic subjects’ appropriate muscle
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activity9 increased for each respective pedal quadrant. The mechanical work done by
plegic leg increased in 75 of 81 instances of subject training conditions without
increasing inappropriate muscle activity.
Instrumented bicycle pedals have been used in evaluating kinetic/kinematic capabilities
for subjects with both healthy and plegic lower extremities [23, 24, 27, 66, 68].
Experimental setups for force sensing has involved a variety of pedal body strain-gauge
based designs which use a deformable body used to measure strain, normal force,
tangential, and some more complex medial/lateral loading. One early example as seen in
Figure 48 is similar to Sharp (1986) using springs between 2 plates to recorded normal
forces from the resulting spring deformation. There have been a range of designs to
measure these parameters such as forces exerted and power generated during short term
ergometer exercise with electric motor driving cranks at given velocity and strain gauges
bonded to crank arms [25]. Wooten & Hull had a range of piezoelectric based designs
that inserted piezoelectric elements between 2 plates to determine load in medial/lateral
plane and derive torque. Alvarez & Vinyolas implemented a fixed-shaft strain gauge
design which measures the force between pedal and spindle shaft. This has been
implemented by replacing the pedal thread with smooth bearing and measuring the force
against spindle shaft, but is not as effective for high loading. Rogers et al used 3-axis load
cells (Delta 660 ATI) to measure pedal forces and 3 optical encoders for crank & pedal
angles. Hoes et al instrumented a using strain gauges bonded to the crank and pedal
assemblies and magnets around an aluminum disk for velocity measure [68]. Broker and
9 Seven leg muscles with EMG recorded from control activation quadrants for the pedal. Inappropriate muscle activity was characterized by using a muscle in a quadrant where it is normally inactive.
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Gregor instrumented the right pedal was instrumented with two Kistler type load cells
(9251 A), which recorded the vertical and shear components of force [67].
Figure 48: Early Pedal-body strain gauge [27] Figure 49: Piezoelectric transdeucer [27]
Figure 50: fixed-shaft strain gauge design [27] Figure 51: A pedal from Penn State University to measure force and pedal orientation during cycling
[27]
Patents & Intellectual Property:
There has been considerable development of ideas and inventions in the field of
stationary exercise bikes, and with the increasing emphasis on adjustability and realism
more ideas are focusing on ways to make a user’s exercise routine more unique and
beneficial.
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Innovations in hardware have allowed a more realistic feeling by increasing the range of
motion of the static bike or handles [69-72]. Some have considered a spring return or
elastomer to provide a degree of resistance, but there does not appear to be any dynamic
haptic feedback adjusted and controlled by the device components.
Devices have also been suggested which can be mounted on a range of different exercise
equipment for broader application [73]. The adjustability of this system suggests
application on several types of exercise machine, but still requires specialized equipment
to provide the necessary range of motion on the target machine.
Considering braking systems to resist motion in the crank, consideration has been given
to dynamically controlling the tension to mimic pedal & crank resistance for real world
physics and dynamics [74, 75]. These devices have excellent capabilities but are non-
transferrable to difference existing exercise bikes and require a complete embedded
system for application.
There has also been development to address interfacing existing exercise equipment with
a computer or electronic device to either translate the rider’s actions as an all-purpose
controller or specifically copy their motions into a virtual environment using selected
gains [76-78].
Using the rider’s level of exertion has been suggested as a means to control the difficulty
of a game interfaced with the bike [79], but mentions heart rate as the only physiological
parameter for the game’s decision matrix of actions.
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Review of these developments reveals that there has not been a device which is adaptable
to any commercial exercise bike whilst also having the same level of parameter
measurement which can distinguish individual force for each appendage and each side of
the body. Most healthy riders are expected to perform roughly symmetrically in their
exercise routine, but for users post-stroke or retraining from another injury or neuropathy
they have distinctive asymmetries in their biking strategy which would not be detected
unless each bike component was individually instrumented.
Table 8: Relevant Patents as Prior Art
Application # Title
455654 Video Game Difficulty Level Adjuster Dependent Upon Player's
663590 Exercising Apparatus Which Interacts With a Video Game Apparatus
09/753778 Variable Pitch Stationary Exercise Bicycle
710244 Apparatus For Connecting An Exercise Bicycle to a Computer
611806 Stationary Exercise Device Having Load-Controlling Braking System
731437 Pedal-Operated Stationary Exercise Device
09/249923 Stationary Exercise Bicycle with Shock Absorption System
08/847879 Foot Pedal Assembly For Exercise Equipment
637835 Foot Pedal For Exercising Equipment
844143 Movement Guiding System for Quantifying Diagnosing And Treating
12/147,694 Stationary Exercise Equipment
479511 Exercise Bicycle Apparatus Particularly Adapted for Controlling Video
09/679193 Apparatus For Removably Interfacing a Bicycle to a Computer
10/601421 Exercise Bicycle Virtual Reality Steering Apparatus
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Commercial Releases:
Most gyms now host stationary bikes fitted with an LCD readout for exercise conditions
like crank rpm, power generated, calories, heart rate, and difficulty setting. Most of these
systems are permanently attached to a single bike and cannot be mounted on existing
equipment.
To add interest for the rider’s routine some models come including a built-in flat screen
monitor for music or television program entertainment (Precor, Woodinville, WA, USA).
This particular model does not have any immersion for a virtual environment, haptic
feedback, or force measurement of the extremities.
Similar systems have been designed as training tools rather than exercise evaluators. To
train user’s reactions and attention for riding a motorcycle or scooter in everyday city
traffic as well as emergency situations (HONDA Riding Trainer, HONDA Riding
Simulator, HONDA motor Co., Ltd, Tokyo, Japan). Some of these devices are USB-
equipped and readily mountable to a desk for interaction with the simulation. These
systems are becoming more widespread but do not have measurement of extremity range
of motion (ROM), physiological state, or force sensing.
Advanced exercise bikes can monitor parameters for tracking a user’s exercise progress
with greater range of motion and interaction than a traditional stationary bike. The user
can experience a more immersive workout by utilizing the upper extremities to navigate
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laterally, initiate turns, and shift gears to increase resistance around the crank (Expresso,
Sunnyvale, CA, USA). Although there is increased range of motion in the handles it still
only provides limited lateral motion in the virtual environment and currently does not
distinguish individual pedal forces.
Some systems have the capacity to connect with each other and allow several riders to
exercise simultaneously in the same environment. This has also been taken one step
further by making the competition the focus of the interaction using a pedal-powered
flight simulator for two-player aerial combat (Dogfight V2, Electronic Sports, Salt Lake
City, UT, USA). The handlebar system stabilizes the user whilst giving them control over
the games functions like flight trajectory and combat systems. This system prototype is
currently limited to recumbent design and is a embedded within a complete exercise bike.
There is a degree of freedom in the handles as an input to the virtual environment, but no
upper or lower extremity force measurement.
The most complex commercial devices with greatest range of motion and instrumentation
simulate a mountain biking experience close enough for professionals to train on year
round like the Trixter XDream (Trixster, Brockton , MA, USA). This device aims at
combining upper body and core strength training with increased range of motion for the
handlebars and ‘front fork’ which allow the rider to lean and twist similarly to navigating
a mountain bike through technically challenging terrain. Data logging is available for
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velocity, power generated and several other parameters, but the system does not
distinguish forces for individual left & right extremities of the body.
Although the majority of these devices have adequate functionality and data capture
capabilities to allow a healthy user to exercise, only a narrow range have been
implemented in physical therapy retraining. Physical therapists benefit from greater
knowledge and tracking of the patient’s capabilities whilst allowing the patient to have a
greater level of device instrumentation and virtual immersion. Many of the more complex
systems are expensive for a clinic, some in the range of $7K-$8K and space can be very
limited to procure several systems.
There are currently a wide variety of stationary exercise bikes commercially or nearly
available. The following section describes examples of comparable technology
implementation from least to greatest functionality and complexity.
Most gyms now host the most straightforward stationary bikes to have an LCD readout
for exercise conditions like crank rpm, power generated, calories, heart rate, and
difficulty setting. To add interest for the rider’s routine some models come including a
built-in flatscreen monitor for music or television program entertainment as seen in
Figure 52 Example A (Precor, Woodinville, WA, USA).
88
Similar systems have been designed as training tools rather than exercise evaluators as
seen in Figure 52 example B. To train user’s reactions and attention for riding a
motorcycle or scooter in everyday city traffic as well as emergency situations (HONDA
Riding Trainer, HONDA Riding Simulator, HONDA motor Co., Ltd, Tokyo, Japan).
Some of these devices are USB-equipped and readily mountable to a desk for interaction
with the simulation. They are both input device and do not track the user’s physiological
state, extremity forces exerted, and lack haptic feedback.
A comparable integrated exercise bike can monitor parameters for tracking a user’s
exercise progress with greater range of motion and interaction than a traditional
stationary bike. The user can experience a more immersive workout by utilizing the upper
extremities to navigate laterally, initiate turns, and shift gears to increase resistance
around the crank (Expresso, Sunnyvale, CA, USA) as seen in Figure 52 example D.
Some systems have the capacity to connect with each other and allow several riders to
exercise simultaneously in the same environment. This has also been taken one step
further by making the competition the focus of the interaction using a pedal-powered
flight simulator for two-player aerial combat as seen in Figure 52 example C (Dogfight
V2, Electronic Sports, Salt Lake City, UT, USA). The handlebar system stabilizes the
user whilst giving them control over the games functions like flight trajectory and combat
systems.
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The most complex commercial devices with greatest range of motion and instrumentation
simulate a mountain biking experience close enough for professionals to train on year
round like the Trixter XDream as seen in Figure 52 example E (Trixster, Brockton , MA,
USA). This device aims at combining upper body and core strength training with
increased range of motion for the handlebars and ‘front fork’ which allow the rider to
lean and twist similarly to navigating a mountain bike through technically challenging
terrain. Data logging is available for velocity, power generated and several others, but the
system does not include force measurement for the handles and pedals.
Figure 52: Commercial stationary bikes & simulators
A: Precor 836i Upright Exercise Cycle
B: HONDA Riding Trainer System
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C: Dogfight V2 Simulator
D: Expresso Stationary Bike
E: Trixter XDream System
Although the majority of these devices have adequate functionality and data capture
capabilities to allow a healthy user to exercise, only a narrow range have been
implemented in physical therapy retraining. Physical therapists benefit from greater
knowledge and tracking of the patient’s capabilities whilst allowing the patient to have a
greater level of device instrumentation and virtual immersion. Many of the more complex
systems are expensive for a clinic, some in the range of $7K-$8K and space can be very
limited to procure several systems. Evaluation of the current commercially comparable
devices necessitate a low cost state of the art system with diverse measurement
functionality, immersion, and adaptability to any current stationary bike in a physical
therapist’s office.
4.3 Design & Sub-Systems
The design and key features of each subsystem is addressed and individually discussed in
the following section.
4.3.1 Handle System
Handle System 4V3
The handle system is an attachment to the stationary bike for evaluation of upper
extremity control and isometric strength. The handle system uses a hydraulic pressure
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sensor to measure the applied differential pressure between chambers on the front and
back of the handle assembly. This is used as an input device for the user to change their
heading in the virtual environment.
Figure 53: Overview handlebar system CAD and physical implementation
Figure 54: Schematic of handle system with major components and sensing of unidirectional of force
A: Handlebar Housing with embedded channels for tubing
B: PVC tubing
C: Watertight attachment ports for tubing to connect to reducing elbows (E)
D: Piezoelectric Hydraulic Pressure Differential Sensor
E: Reducing Elbows
F: Handle Caps with embedded channels for tubing and built-in rungs for adjustment straps
G: Tubing Plug
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Figure 54 indicates how application of force (blue arrows) on one chamber causes the
tube to compress and build up pressure at one end of the pressure sensor. The sensing
area of the handle is the surface area of the three exposed tube sections between the
handle caps which is contacted and compressed by the user. A key design goal was to
minimize the loss of pressure transmission from the connections to the sensor during load
application. When a load is applied over the pressure sensing area, any tubing not under
direct compression will expand, causing loss of pressure transmission. Therefore tubing
under the handle caps has been constrained and tube lines outside of the handlebar
housing (C, G) has been minimized and plugged.
Sensor Selection:
The sensor selection and overall handle design were concurrent processes. The primary
function of the handle system was to measure the differential force between the front and
back surfaces of the handle and transmit them as an input for steering motion in the
virtual environment. This subsystem was designed for robust & comfortable functionality
regardless of:
• Dynamic grasping configuration during use • Anthropomorphic range of adult hand widths • Shear forces resulting from severe pronation of the hand • Inconsistent center of force during application • Uneven force distribution during use • Different force ranges per phalange
These criteria were satisfied by designing a double-chamber hydraulic pressure
measurement system. By then connecting the two chambers with a sensor the output from
the entire system was a single voltage, regardless of application surface.
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Figure 55: Omega PX26 hydraulic pressure differential sensor
Hydraulic Omega Physical Properties
Thickness 0.50" (12.7mm)
Length 1.35" (34.4mm)
Width 0.31" (8mm)Hydraulic Omega Typical Performance
Linearity Error <+/‐ .25%
Repeatability <+/‐ .2%
Response Time 1 microsecondPressure 0‐250 psi. (1.72 MPa)
Three of hydraulic pressure sensors were compared for availability, simplicity, and cost.
The Omega PX26 sensor (Omega, Stamford, CN, USA) was selected as the best
combination which satisfied these three categories for the design criteria.
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Figure 56: Overall view of handle with detail on channel housing and handle cap
A: Tubing Plug
B: PVC Tubing
C: Handle Cap with embedded channels to guide and constrain tubing
The tubing (B) is constrained inside the channels between the Handlebar Housing and the
Handle Cap (C). The dimensions and cut depth for the channels (C) constrain the tubing
clamped underneath in a slightly compressed state. The channels are designed to
constrain the ends of the tube using their minimum bend radius and provide an outlet for
the plug / reducing elbow connector.
95
Since the tubes are pre-filled during assembly this compression causes a pre-load on the
tube plugs and slight expansion of the unconstrained tube. A filling protocol was
developed to account for this pre-load so that the initial pressure inside each chamber is
as close to zero as possible.
Figure 57 below shows three views of the tube & channel paths in the handle system. The
handle housing was designed with a diameter to provide the greatest ergonomic comfort
for grasping whilst allowing the user to comfortably maximize their isokinetic strength.
Figure 57: Detail views of tube arrangement on front and back of handle
Each of the two hydraulic chambers is comprised of a single length of tube which is
guided along channels in the housing and handle cap to run back and forth and maximize
the sensing surface area for each chamber. The section of tube underneath the handle
caps is rigidly constrained to prevent loss of pressure from tube expansion.
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Figure 58: Detail view of channel arrangement on handle body
Figure 58 above shows the handlebar housing with embedded channels for tubing and
cavities for fasteners. In order to maximize the effective sensing surface area three
channels were designed into the housing with loops at each end according to the tube
minimal bend radius (16mm) and reorient the tubing without kinking.
Within the simulation the handlebars control the trajectory of the virtual rider. The
differential forces from the left and right handles are subtracted after being acquired in
the practitioner’s interface and the final net force steers the virtual bike through the
simulation.
Handle System Previous Design Iterations
The main emphases for functional assessment of previous iterations were compliance,
connectivity, and form closure from discussion of these grasping characteristics. The
grasp taxonomy resulting is best employed when the user has a choice of how to pick up
and manipulate an object rather than being constrained to a single orientation. But for
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exactness the definitions will be used here to quantify the handlebar interaction with the
rider’s hands. [60]. Two major design iterations of the handle system are detailed below.
Handlebar 3
Figure 59: Handle 3 prototype single channel detail views
A: Handle Housing
B: Existing Handle
C: PVC Tygon Tubing
D: Nylon-Braided PVC Tubing
E: Hydraulic Pressure Sensor
F: Load Paddle
Handlebar 3 wrapped the tubing around a cylindrical housing and added an extension of
stiffer braided tubing for connection to the sensor10. The stiffer tube had a much larger
bend radius (25.4mm) thus required the overall length of the handle to be increased by
55%. It also has a much higher spring return so became more difficult to effectively
constrain inside the channel.
10 Note that for the final prototype iteration constraining the non-sensing sections of tubing was accomplished by using the handle caps (Figure 56).
98
The connection point between the stiffer and softer tubing was problematic since the two
materials required different diameters for the barbed plug ends. This led the coupling
interface to be prone to leakage under the higher range of grasping pressures. A
comparison of the tubing material properties is found in Table 9: Comparison for Tubing
Material PropertiesTable 9 below.
Table 9: Comparison for Tubing Material Properties
Material Property
Silicone Rubber
Braided Nylon PVC
Polyurethane PVC Tygon
Durometer 50A 73A 95A 55A Bend Radius 8mm 50mm 13mm 16mm
Visability Semi-Clear White
Semi-Clear Clear Clear
Tensile Strength
7.58 MPa 17.49 MPa 41.37 MPa 11.37MPa
Operating Temperature
-70°C to 200°C -4°C to 66°C -40°C to 74°C -50°C to 74°C
Max Pressure 0.103 MPa at 22°C
1.72 MPa at 21°C
1.103 MPa at 24°C
0.172 MPa at 73°C
Devices Used Testbed 1 Testbed 2 Handle 3
Handle 3 Handle 4V1 Handle 4V1 Handle 4V3
There did not appear to be any significant different in the application of force between
the chambers on either side of the braided tubing, but the forces applied were too low to
be conclusive (see section 4.5 for details).
Ergonomic evaluation of the handle indicated that adjustability in the angle between the
two chambers was necessary for patients with different degrees of pronation and grasping
strength. Handle prototype 3 had both sides rigidly mounted at 180 degrees with sensing
area limited to a single channel. The user interaction with the deformable tubing also
provided a mild haptic feedback because of the elasticity of the material under load and
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greater ergonomic comfort as it self-contours to the hand’s topology. For these reasons it
was concluded to remove the rigid load paddles for the next iteration.
Figure 60: Detail views of handle 4V1 prototype with multi-channel tubing and detail of sensor housing compartment
A: Hydraulic Housing
B: Sensor Housing Compartment
C: Extended Tube and Fittings
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To increase the width of the sensing area, each hydraulic chamber was extended and
wound into the embedded channels to create three parallel tube lengths. This could
potentially have also been accomplished with a three-port manifold tube fitting for a
more compact design, but would have increased the overall complexity and susceptibility
to leakage11. The blue arrows in Figure 60 indicate direction and application of pressure
through each chamber to the sensor.
The Tube ports for the elbows were extended to the sensor at the ventral side of the
handles, located centrally under the assembly and protected with an enclosure. Reducing
fittings were required between the tubing and sensor, and slots embedded to the
compartment cavities secured them in place to maintain a close seal with the sensor at
higher pressures.
Trapped air bubbles were a significant challenge since the sensing accuracy relies on the
chambers’ interior being elastic but incompressible. When generating the protocol for
filling and connecting the hydraulic components coloring the liquid greatly improved
visual detection of trapped air. Several water-soluble dyes, paints, and inks were
evaluated for clarity, uniformity, and mixing consistency inside test chambers12.
Each design iteration had a period of ergonomic evaluation for both an upright and
recumbent exercise bike. When mounted to the handlebars for use on a recumbent
exercise bike the wrist grasped the handle in an abducted power grasp position,
contacting the abductor minimi digiti muscle with the handle cap. Further evaluation 11 Potentially 45mm of length could have been removed at one end of the handle. For the prototyping phase, stereolithography was used to fabricate the handles and could have generated the geometry for embedded manifolds. However the nature of the material used would have softened over time from direct contact with water. 12 The tubing material was also assessed for staining from prolonged exposure to the inks & dyes.
101
indicated that for use with a recumbent exercise bike the sensing area length would need
to be increased from 90mm to 120mm to avoid this collision. The distance of the sensor
compartment (Figure 60 Item B) from the housing was also insufficient because it
collided with the knuckles of the digitus secundus manus and digitus medius.
Handlebar 4V3: Final Prototype
The final prototype in Figure 61 has an extended sensing area for the three tube lengths
and the more fragile sensing components & connections have been moved to one side to
avoid uncomfortable contact with the user’s hand. This minimizes extraneous
unconstrained tubing in the system. The sensor system has been mounted on the bike
handlebar with high-friction padding and adjustable Velcro straps.
Figure 61: CAD rendering and physical prototype handle 4V3 in application
4.3.2 Pedal System
Pedal Design
The pedal system uses a load cell to monitor forces from the rider’s lower extremities
during pedaling. These sensors monitor maximum tensile/compression loads and
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asymmetry in the user’s pedaling forces. The average force readings between both pedals
must be symmetrical to keep the virtual rider vertical within the simulation. Range of
motion of the ankle is monitored by an accelerometer embedded in each pedal to detect
angle of tilt relative to a horizontal datum. Vibrating elements have also been included to
provide haptic feedback to the user, triggered by events from the simulated environment
like riding off the path. Rotational velocity of the crank arm propels the virtual rider
forward is controlled by the velocity of a latching Hall Effect sensor passing by four
magnet posts.
Figure 62: Overview pedal system
An instrumented pedal was designed to measure lower extremity forces and range of
motion during user interaction with the exercise bike. The pedal system was required to:
• Measure Compressive and Tensile Forces from the Feet • Measure Range of Motion for Dorsi and Plantarflexion During Exercise • Measure Rotational Velocity of the Pedal • Exert Haptic feedback to the Foot • Securely hold The User’s Without specialized Footwear • Interface Easily with any commercial Stationary Bike
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To allow the pedal to easily attach to a commercial bike, the pedal design was centered
around an existing pedal with the standard 9/16” x 20 thread (Wellgo M-21 ATB,
Wellgo, Taichung Hsien, Taiwan) which fits all adult bikes with two and three-piece
crank assemblies. The raceway of these pedals has built-in roller bearings and four screw
attachment points for a cage or toe clip.
Figure 63: Detail components view of pedal assembly
A: Vibrating Elements H: Pedal Raceway
B: Fittings for Mounting Ladder I: Hall Effect Sensor
C: Screw & Spring Pre-Load Assembly J: Compression Load Cell
D: Pedal Counterweight block K: Binding Ladder
E: Accelerometer Mounting Bracket L: Binding Padding
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F: Accelerometer N: Intermediate Plate
G: Foot Plate
To secure the user’s foot to the pedal a specific binding scheme was required. A readily
adjustable, robust, comfortable fit was vital to secure the metatarsal-phalanges joint just
above the pedal’s axis of rotation but not require specialized footwear for the user other
than exercise shoes. It was especially important that the bindings were able to transfer as
much of the tensile load as possible without deformation. A range of platform, quill, and
clipless (cleated) pedal configurations were examined, but fit was successfully achieved
using Flow Flite 4 snowboard bindings (Flow, San Clemente, USA). These attached
across the dorsal side of the wearer’s foot from the base of the internal and middle
cuneiform down to the middle of the metatarsals.
The binding ladder attachment Figure 63 ratchets into the binding buckle for fit
adjustment and is compatible with several sizes of bindings to fit the anthropometric
range of adult and adolescent riders.
Figure 64: Application detail and pedal cross-section
A: Foot Plate
B: Delrin Force Block
C: Intermediate Plate
D: Load Cell
105
Application of force on the foot plate needed to be detected by the load cell directly
underneath the raceway. To avoid modification to the raceway, delrin force blocks
(Figure 64) were designed to transfer the load around the raceway shaft and still maintain
alignment by sliding in grooves on either side of the U-Channel. The base of the force
blocks attaches to a 3/16” (4.75mm) thick steel intermediate plate which directly contacts
the load cell. Deformation of the steel plate contact site was determined via FEA to be
under .5mm for the applied load of 113N.
The forces on the plate are measured by a single-axis low profile compression load cell
(Model 13, Honeywell, Morristown, NJ, USA). Four bolt & spring assemblies provide a
collective 50lb (222.4N) pre-load compression on the pedal system to enable the single-
axis load cell to detect tensile forces in the pedal. The resulting offset for the load cell
voltage is zeroed in software. This enables measurement of tensile force up during
pedaling to this pre-load max, and compressive forces up to 450lbs (2001.7 N).
106
Section 1.3.2: Sensor & Electronics Implementation
Figure 65: Detail view of pedal interior assembly
Load Cell
The load cell implemented was a Honeywell
Model 13 Subminiature Load Cell (Honeywell,
Columbus, OH, USA). The compact size and
high durability were appropriate for the pedal design when compared to 11 other sensors
examined. The selection criteria were also simplified by only requiring compression
rather than bi-directional sensing because of the pre-load assemblies.
Vibrating Element
To provide haptic feedback to the rider, vibration elements were implemented in the
pedal bindings. The most compact shaftless vibrator was the Precision Microdrives 310-
A: Pedal Raceway
B: Hall Effect Sensor
C: Spring Pre-Load Assembly
D: Compression Load Cell
E: 2-Axis Accelerometer
F: Delrin Force Block (x2)
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108
(Neodymium disc .335", 8.5mm diameter) were mounted to the exercise bike housing in
opposite alternating poles to mark top dead center, 90° CW, 180° CW, and 270° CW. As
the pedal passes next to one of the posts the Hall Effect sensor registers the change in
polarity of the magnetic field and switches its signal for the digital input. Each time it
registers a change in the field it has travelled 90°. The time in between the magnets is
used to calculate rotational velocity of the crank. For the range of motion of a human leg
the Hall Effect sensor was able to detect the field of each post.
The pedal rpm input is used to propel the virtual bike in the simulation. Since there is no
instrumentation on the stationary bike for gearing or wheel radii this does not yield a
velocity value by itself. Therefore the practitioner may adjust a multiplier gain to the
patient’s rpm to generate an artificial velocity in the simulation.
4.3.3 Additional Electronics
Heart Rate Monitor System
A wireless heart rate receiver was necessary to drive a pace rider in the virtual
environment. The RE07L Wireless Receiver Module and T31 coded elastic chestband
(Polar Electro Inc., Lake Success, NY, USA) were selected. The chestband is worn
during exercise with the transmitter in skin contact just below the center of the sternum,
detects each heartbeat, and outputs a pulse for each heart beat. The combination of these
two components fulfills the selection criteria for the heart rate monitor in a cost-effective
way:
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• Sensitivity unencumbered by activity level • High reliability under elevated levels of moisture and sweat • The wearer is not hindered in performing their tasks from discomfort or
constrained motion • Low power and bandwidth requirements
The system in this device has a coded communication to improve noise reduction and
cross-talk from other sensors by automatically remodulating the communication
frequency when in close proximity to the chestband. It has an operating range of 80-
105cm and operating frequency of around 5kHz.The chestband outputs three pulses for
each heart beat detected, of which only one needs to be detected by the receiver to
register a heartbeat. The highest heart rate for a healthy human is on the order of 240
beats per minute (4Hz, 250ms window each pulse) which is within the Polar system’s
operating frequency of 200ms. As part of the remodulation sequence the chest strap must
begin within 50cm from the receiver for approximately 5 heartbeats during startup of
each exercise session.
Before an exercise session, the practitioner will have set the target heart rate of the
patient. This target heart rate controls the position of a pace rider which the patient must
ride next to throughout the exercise. The difference between the target heart rate and the
measured value from the patient determines the location of the pace rider relative to the
patient’s virtual rider. This location may be in front or behind, depending on which value
is greater.
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Signal Amplifiers
Strain gauge amplifiers (Industrologic, St. Charles, MO, USA) were used to amplify the
signal outputs from the pedals’ load cells and handlebars’ pressure sensors. These
amplifiers use a full Wheatstone bridge and have an operating range of 8-30V DC with a
built-in 5V regulator for the sensor excitation. They can operate in single-ended mode
(for the load cells) by bridging the GND and V- terminals or bi-polar mode (for the
handle bar pressure sensors) using a negative voltage supply.
Figure 67: Schematic of SGAU strain gauge signal amplifier
The SGAU circuit assembly has a fixed gain resistor of 100 ohms in series with a 1K
trimmer potentiometer (VRG), allowing the amplifier gain to range from 1000 with the
trimmer fully clockwise (100 ohms) to 90.9 with the trimmer fully counterclockwise
(1100 ohms). The voltage signal offset may be adjusted by turning the VRO terminal.
The span of the load cell amplifiers were shunt calibrated to each load cell using a 59kΩ
resistor to bridge the E- and S- terminals and then adjusting the voltage offset to zero
when the resistor was removed.
Data Acquisition System
The data acquisition system used in this device was the NI USB DAQ 6008 (National
Instruments, Austin, TX, USA). This device afforded the flexibility of a range of
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analogue and digital input devices, whilst also supplying a +5V excitation to the smaller
devices like the heart rate monitor and vibrating elements. It was connected with a
common GND to the amplifier units for the handlebar and pedal force sensors.
Signal & Power Box Hardware
The power box used in Figure 68 was a LOGISYS ATX12V (LOGISYS, Pomona, CA,
USA) to provide GND, +5V excitation, and ±12V excitation to the system. Inside the
signal box four amplifiers are connected to the handlebars and pedal load cells. These
four elements are tethered to the external sensors through the front of the housing along
with the pedal accelerometers, hall effect sensor, vibrating elements, and heart rate
receiver module.
Figure 68: Overall view of power and signal boxes
The USB DAQ system is also contained in the signal box, connected to the analogue &
digital sensor ports, and connected with common GND terminals to the power source and
amplifiers.
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4.3.4 Software
Two LabView Virtual Instruments (VIs) were created for the bike system; the Signal
Interface VI and the Main Interface VI. Both of these VIs use User Datagram Protocol
(UDP) to transmit information from the VI to the Virtual Environment generated by
software from a third party developer. The flow of information throughout the system is
outlined in Figure 69 below.
Figure 69: Information communication diagram
The system is first configured by the Practitioner using the Configuration Interface within
LabView. Once an exercise session has begun, information from the sensor on the bike
is transmitted via the Data Acquisition (DAQ) card to the LabView VI. The data is then
processed in LabView and sent via UDP sockets to the third party VR software to control
the user’s rider in the simulated environment. Post processing of the data is also logged
into an Excel Spreadsheet for later analysis.
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Signal Interface:
The Signal Interface was used to prototype the third party virtual reality simulation
during concurrent development of the hardware systems. It is designed to send signals
using UDP that are identical to the signals that the actual sensors send on the device. The
UDP code that is used in the signal interface is the basis of the UDP code in a UDP Sub
VI. A screen capture of the signal interface front panel can be seen below in Figure 70.
The bike system includes eight sensors (hardware is discussed in 4.3.1 - 4.3.3) all of
which are emulated using the signal interface.
Practitioner Main Interface:
The Practitioner Main Interface (hereafter referred to as simply “interface”) has several
components and objectives, primarily housing all the controls and displays that the
practitioner may use during a session. The interface is used to acquire all the sensor data
from the DAQ card, display it in real-time, and log the data into two different files for
later evaluation. The further function of the interface is to send modified data to the VR
simulation so that is can provide accurate and updated visual feedback to the user.
Because of the complicated nature of these objectives it was important to use the Sub VI
feature of LabView to simplify and streamline designing the interface. A Sub VI can be
compared to an object in Object Oriented Programming (OOP). These Sub VIs are all
executed simultaneously inside the main ‘while’ loop until the practitioner ends the
session. The loop contains a counter that is used in several of the Sub VIs as well as a
delay timer to have the loop run at 100Hz under ideal conditions (the loop may be slowed
due to computation speed or other factors).
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The data is acquired using tasks set up to the appropriate lines and ports of the DAQ card.
This data is then split and sent to the corresponding Sub VIs for any necessary processing
or manipulation (all of the Sub VIs are discussed in the following sections). Then the
data is sent through the data logging and communication Sub VIs to be recorded and used
in the VR simulation respectively. Below in Figure 70, is a screen capture of the
interface’s front panel.
Figure 70: VRehab main interface front panel
The front panel can be broken up into sub-elements for ease of explanation as follows.
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Figure 71: Loop and data logging controls
The arrow above the stop button starts the interface, the grayed out stop sign icon is the
emergency stop button which ends data acquisition without cleanly finishing the loop.
The larger stop button is used by the practitioner to stop the interface between sessions of
normal operation. The zero sensors button is used to zero any offset, normalizing all the
sensor readings to prevent drift as well as look at comparison data. The file name and
record button are used for naming and recording the data files.
Figure 72: Handlebar display and controls
The filler bar is used to adjust the sensitivity of the handlebars in the VR simulation as
seen left Figure 72. The graph displays how the handlebar data changes over time. The
left and right handlebar numeric displays show the real-time readout of the data as the left
and right net handle forces are displayed real-time. The override button is used to null
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the handlebar signal being sent to the VR simulation and cause the virtual rider to go
along the path centerline. This function allows the practitioner to isolate exercises for
each patient.
Figure 73: Pedal force display and controls
The graph in Figure 73 shows the change in the pedal force data over time and the two
numeric displays beneath the graph show the real-time values. The override button nulls
the signal being sent to the VR simulation and forces the virtual rider to remain vertical.
Figure 74: Pedal angle display
The pedal angle is displayed using two gauges that span from 90° to -90°. There are no
controls associated with the angle on the front panel since it does not affect any of the
parameters of the virtual environment. To the right of the pedal angle display there are
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the revolutions per minute (rpms) and velocity controls and display as seen in Figure 75
below.
Figure 75: Velocity and RPM controls and display
The graph displays the change in rpm and velocity data over time and the numeric
displays beneath the graph show the real time data. The velocity button forces the
velocity data being sent to the VR simulation to never drop to zero. This is to maintain a
positive reinforcement to the patient in the event they are unable to pedal continuously.
The gain setting controls the velocity output for the VR simulation based on the rpm
measurement.
Figure 76: Heart rate and vibration controls and display
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The heart rate is displayed by a rectangular light that is illuminated red when a beat is
detected from the chestband. It is also displayed as beats per minute (BPM) beneath the
light display. The vibration button is used to switch control of the vibration elements
between manual control and simulation control. Manual control uses the two slider bars
to adjust the frequency of vibrations in the elements. Simulation control activates the
elements when data is read from the VR simulation via UDP communication.
Figure 77: Minimum and maximum controls and display
The minimum and maximum values are displayed for each sensor and can be reset using
the reset button. The save button saves the current values into a spreadsheet file. To
calculate the minimum and maximum values of each sensor a Sub VI was created.
VR Simulation:
The third piece of software that was created for the system is the VR simulation that was
created by a third party developer. The purpose of the virtual environment is to provide
the user of the system with visual feedback on their performance. Initial parameters need
to be set on the VR Simulation Menu before a session can begin (Figure 78).
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Figure 78: VR simulation menu
The default starting point is at the beginning of the loop but the simulation can also be
started at one of the checkpoints at are spread throughout the virtual environment. The
second option on the menu is to set the level of riding difficulty to set the width of the
path that must be followed. The next two options control the distance of the pace rider as
a function of the user’s target heart rate. The last two options allow the practitioner to
either start the simulation with these settings or quit the program. Once the session is
started the simulation begins, and the environment changes to Figure 79 below.
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Figure 79: VR Simulation during a Session
The upper right corner of the simulation displays a map of the virtual environment, with
the user (red dot) and various checkpoints (yellow dots). Below the map the
instantaneous heart rate of the user is displayed. The virtual environment is divided into
two regions: the sandy tan path that the path that the user traverses and the green rough
that surrounds it. Data that is sent from the UDP Sub VI of the interface to the VR
Simulation is used to control the virtual rider. The rpm data controls the speed, the
handlebar force data controls the heading, and symmetricity of the pedal load cells
control the tilt of the player.
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4.4 Testing & Experimental Setup
Handle System Testbeds
To evaluate the capabilities of the sensor and tubing system, two proof-of-concept
testbeds of varying complexity were designed. The performance of these testbeds was
evaluated under varying load magnitude, load location, and chamber complexity
(addition of tube fittings) before modeling the complete handlebar prototype. Testbed 1
(Figure 80 below) is the simplest, idealized two-chamber hydraulic system design.
Figure 80: Testbed 1 to evaluate sensor with inline hydraulic chambers
A: Tube & Sensor Housing
B: Hydraulic Pressure Sensor
C: Load Paddle
D: Starting Load Location from Sensor Port
Testbed 1 has two straight in-line hydraulic chambers connected directly to the pressure
sensor and plugged at opposite ends. The tube material was semi-clear silicone rubber
(see Table 9). The tubes were constrained by the housing on 62% of their surface area
and an additional 29% when in contact with the load paddles. The load paddles provide a
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steady horizontal platform for even distribution of weight over the entire length of the
tube. Distribution of the force is necessary to normalize application surface area and
constrain the tube sections not in direction contact with a load. They are not directly
attached to the housing but slide in tracks on either side of the tube to remain vertically
aligned when loaded.
The omega pressure transducers do not require a conditioning protocol and could readily
output voltage readings when connected and sealed with the system. Any pre-load
pressure between the chambers was removed by a software tear before calibration.
Figure 81: Testbed 2 to Evaluate Sensor with Adjacent Tube Arrangement
A: Tube & Sensor Housing
B: Load Paddle
C: Detail of Paddle & Tube Housing Cross Section
D: Starting Load Location for 20mm Away From Elbow Port
Testbed 2 in Figure 81 has the same housing geometry, paddle geometry, tubing material,
and plug caps as testbed 1 but introduced tube elbow fittings and a tube extension. The
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configuration of this tubing is closer to what the final handle configuration was expected
and it was necessary to see what loss (if any) of pressure transmission occurred by
introducing the elbows and extra tubing for a more complex implementation. The
chambers for testbed 2 were more problematic for evacuation of air bubbles. This was
solved by adding a small amount of surfactant to the distilled water (<2%) to ease the
removal of trapped air.
Protocol for Tests Conducted on Testbed 1 & Testbed 2:
• Loading Linearity: Step increases in mass were applied at the center of one chamber
using the 10mm long paddles to stabilize the load. A Sensotec SC00 Signal Amplifier
(Honeywell, Columbus, OH, USA) was used in conjunction with a desktop
multimeter to record voltage out readings. The test was repeated five times for both
chambers and results were averaged. Thin & thick paddles (2mm, 4mm plate
thickness) were both tested. System was allowed to settle for 1 minute between steps,
and 2 minutes for unloaded state between trials.
• Inter-Chamber Symmetry: Step increases in mass were applied at the centers of both
chambers using the 10mm long paddles to distribute them over the entire tubing
length. A Sensotec SC00 Signal Amplifier (Honeywell, Columbus, OH, USA) was
used in conjunction with a desktop multimeter to record voltage out readings. The test
was repeated five times for each mass and results were averaged. System was allowed
to settle for 1 minute between steps, and 2 minutes for unloaded state between trials.
• Load Location: One mass was placed on a single chamber using the 10mm long load
paddles. Voltage responses were recorded as the mass was moved in 10mm
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increments away from the sensor inlet, starting closest at 17mm (Point D, Figure 80
& Figure 81). Five trials for each of four masses (50g – 1000g) were recorded. Tests
were conducted for thin & thick paddles. The system was allowed to settle for 1
minute per load location, and 2 minutes for unloaded state between trials.
Handle Prototype System Calibration
The handlebars were calibrated to match the force applied over the tubes to the voltage
resulting from the pressure in the hydraulic chambers. A calibration paddle was
fabricated with an interior contour to match the shape of the three tubes to evenly
compress them over the length of the sensing area (See A, Figure 83). This is similar to
the calibration sequence used by Chadwick et al. with a 6 member cylindrical beam
dynamometer [61].
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Figure 83: Calibration schematic, hardware, and procedure
A: Tube-conforming Paddle
B: Paddle Backing
C: Single Hydraulic Chamber
D: Steel Cable
E: Eyelet Coupling
F: 2-Axis Load Cell
Figure 82: Handle 4V3 calibration paddle
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The calibration sequence consisted of evenly aligning the paddle interior grooved surface
against the chambers and compressing them by 91N for 30 seconds13. The average forces
and voltages over this period were matched with the tensile force from the load cell
(Omega LCFA-500, Omega, Stamford, CT, USA) to determine Force/Voltage ratio. Any
initial pressure offset was electronically adjusted to zero and the load was applied and
both chambers on each handle were individually calibrated.
Protocol for Tests Conducted on Handle 4V3 Prototype:
A series of tests were conducted to validate the design of Handle 4V3 and also evaluate
its capabilities as an input device for the virtual environment.
• Grip Oscillations from Steady Pedaling: During normal pedaling motion oscillating
loading patterns in the isokinetic grasping forces occurring from trunk rotation and
flexion/extension of the legs have been observed [27]. To assess symmetricity and
loading between the two handles, force patterns were recorded and compared for left
& right hands. The subject pedaled without viewing the VI or simulation and pedal as
symmetrically as possible. Three 1-minute trials were conducted with a 1 minute
break between trials.
• Linear Increase in Isokinetic Grip: While sitting in the system but without pedaling,
the subject grasped the handles without viewing the VI or simulation. Over a 30-
second period they linearly increased their isokinetic grasp on both handles up to 70%
13 9% maximum comfortable loading combined isokinetic grasp with shoulder reaction force. See section 4.2 for further details on grasping forces.
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of their maximum comfortable force. Subjects were allowed to take three unrecorded
practices beforehand. Then three 30-second trials were conducted with a 1 minute
break between trials.
Protocol for Tests Conducted on Pedal System:
A test was conducted to examine the loading pattern of the left and right feet during
steady pedaling.
• Steady Symmetrical Pedaling: During normal pedaling motion characteristics
oscillating loading patterns have been observed. To assess symmetricity and loading
between the two pedals, force patterns were recorded and compared for left & right
feet. A healthy subject pedaled as symmetrically as possible without viewing the VI
or simulation.
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4.5 Data
Testbed 1&2: The data in the charts below indicate the performance of the basic sensor
system under ideal conditions for inline and offset chambers.
Loading Linearity:
The data in Figure 84 indicates that under increasing loads the system has high linearity
with comparably high regression values for both thin & thick paddles. After the software
tare a non-zero Y-intercept has still been recorded for both paddles but is close to zero. In
this experiment the zero load offset errors were 1.6% and 1.7% of the maximum applied
loading for thin and thick paddles, respectively.
Figure 84: Mass vs Voltage Data for Testbed 1 for two different paddle thicknesses. Data has been averaged for results from both chambers over 5 trials each.
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Data for testbed 2 still exhibits excellent linearity; and the regression values are only
minimally lower than for testbed 1. In this experiment the zero load offset errors were
1.18% and 4.93% of the maximum loading for thin and thick paddles, respectively.
Regression values increased for the thin plate and dropped for the thick plate, the
differences are on the magnitude of less than 1%.
Figure 85: Mass vs Voltage Data for Testbed 2 for two different paddle thicknesses. Data has been averaged for results from both chambers over 5 trials each.
Inter-Chamber Symmetry:
When loaded symmetrically on both chambers the ideal net voltage will be zero. The
loading was applied evenly and consistently for both chambers. The data presented below
has been averaged from 5 trials for mV offset. The peak uneven measure of 2mV for the
thick paddle corresponds to an error of 71g (compared with regression values from
Figure 84).
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Figure 86: Concentrated loading on Testbed 1 simultaneously on both chambers
The loading was fairly consistent for both chambers, performance was similar to Testbed
1 in displaying erratic behavior for the lower masses. The peak uneven measure of
1.28mV for the thick paddle corresponds to 50.8g, which is a smaller error than testbed 1
but comparable.
Figure 87: Concentrated loading on Testbed 2 simultaneously on both chambers
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In Figure 88 below applied loads were moved along the chamber away from the sensor to
track sensitivity drop from further distance. The ideal performance is a straight horizontal
line for each mass, increasing to match the linear loading voltages from Figure 84.
Figure 88: Mass loading location vs voltage response for thin paddle Testbed 1. Data has been averaged for results from both chambers over 5 trials each.
Figure 89: Mass Loading location vs voltage response for thick paddle Testbed 1. Data has been averaged for results from both chambers over 5 trials each.
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Testbed 2 showed good linearity and consistency for the lower masses regardless of
proximity to the sensor.
Figure 90: Mass loading location vs voltage response for thin Paddle Testbed 2. Data has been averaged for results from both chambers over 5 trials each.
Figure 91: Mass loading location vs voltage response for thick paddle Testbed 2. Data has been averaged for results from both chambers over 5 trials each.
133
Overall the low mass responses for testbed 2 had lower voltage readings than testbed 1,
but for higher loads (like 500g & 1000g) the average voltages were higher in loading
location.
Handle 4V3:
All data for the following three tests has been collected via attachment to a recumbent
stationary bicycle (Biodex, Shirley, NY, USA). Data was collected from a subject who
was a right-hand dominant healthy adult male with no previous cognitive or physical
impairments. It is important to note that the stationary bike used for this testing is fitted
with a friction brake which cannot be disengaged, but was kept consistent for friction
forces.
Grip Oscillations from Steady Pedaling: Oscillating force readings on the handles were
anticipated. The frequencies of the left and right handle forces were expected to be the
same and that frequency should correlate to the pedals’ rpm. Figure 92 below displays the
revolutions per minute (rpm) of the crank along with the handle forces. The results from
Trial 2 are shown below, and trends are representative of all three trials in this test. The
data has been sorted to remove the ramp-up period data for the pedaling motion. RPM for
this test was steady averaging 93 rpm.
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Figure 92: Handlebar forces vs pedal rpm
As seen in Figure 93 below, amplitudes of peaks for left and right hands are close but
have consistent differences. The left hand peaks (compressive forces) are consistently
lower by roughly 20% but troughs (tensile forces) are comparable for both.
Figure 93: Handlebar forces close-up comparison
The characteristic shapes of both red and blue curves have clear increases and slower
decreases in force for each period. Positive values indicate an upward ‘pulling’ force on
the underside of the handle. Negative values indicate a downward ‘pushing’ force on the
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topside of the handle. Loading patterns for left and right handles have been isolated
below.
Figure 94 A & B: Right Hand (A) and Left Hand (B) forces during steady pedaling motion for Trial 2
For all three trials the loading patterns differed from left to right hands. But the trends for
each hand were consistent from one trial to the next.
Linear Increase in Isokinetic Grip:
The results were anticipated to be a roughly linear increase from zero to a force 70%
MCL, then a sharp drop off. Below are averaged results for the three loading trials,
normalized and aligned at the peaks for the 30 second cycle. Peak forces perceived at
70% MCL were within 2.8% of each other (18 lbs, 80 N) for both hands. The left hand
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exhibited a smoother transition to peak and smoother drop (unloading) to zero. Right
hand had a sharper increase, decrease. Both curves have a 2.5 sec resting value at the end.
Figure 95: 0-70% MCL for grasping during rest averaged for three trials
Steady Symmetrical Pedaling:
A healthy adult female subject pedaled in steady motion at 38 rpm for the 4 minute
duration of data collection.
Figure 96 below is a close up view of left & right pedal forces during symmetrical
pedaling. Peak loadings are ½ period apart for the 180° offset between the crank arms.
Positive values indicate compression forces, negative values indicate tensile forces. Peak
compression force magnitudes were smaller for the left foot, maximum tensile forces
were greater for the left foot than the right.
137
Figure 96: Left Pedal (Blue) Right Pedal (Red) Loads during 5 Seconds of steady symmetrical pedaling
Normalized curve samples are shown below for one rotation of both pedals. Curves were
normalized at zero force point as crank TDC. The amplitude of forces for both pedals is
22.5 lbs for compression, with greater tensile forces exhibited by the left pedal.
Figure 97: Normalized Curve for Left & Right Pedal Forces for 1 Rotation
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4.6 Analysis & Discussion
Loading Linearity:
The data in Figure 86 for testbed 1 had excellent linearity for loads up to 3kg. The thin
and thick paddles have different flexibility but their short 10mm lengths do not seem to
greatly affect their performances (r2 values for linear regression differ on the 3x10-3
magnitude). It is possible that the slightly higher linearity can be attributed to higher
paddle rigidity to distribute the load more evenly. Identical slope values and similar Y-
intercepts indicate comparable performance in this test application.
Data for testbed 2 still exhibits excellent linearity (Figure 85), however the regression
values are relatively lower than for testbed 1. In this experiment the zero load offset
errors were 1.18% and 4.93% of the maximum loading for thin and thick paddles,
respectively. Compared to the responses from testbed 1 the slopes of the curves were
identical but had different y-intercepts. This indicates that the initial response of the
sensor is comparable between the testbeds, but the pre-load changes from the elbow
hardware fittings and extra tube despite using the software tare. Maximum voltage
difference for 3000g between testbed 1 & 2 was 4.65% and 4.66% higher for thin & thick
plates respectively in testbed 2 than testbed 1. Regression values increased for the thin
plate and dropped for the thick plate, although the differences are on the magnitude of
less than 1%14.
14 Keeping in mind that the extra tubing was only constrained on 68% of its surface area. This shows that even a soft tube can possibly maintain a good response despite not being rigidly constrained.
139
Inter-Chamber Symmetry:
A net voltage of zero means that pressure from both chambers is equal and cancels each
other out. This test evaluates the hysteresis of the chambers which could be affected by
handle orientation when mounted on the physical bike handle. The loading was consistent
for both chambers, indicating that the hydraulic sensor performs symmetrically for both
sides. For testbed 1 both curves were erratic for loads under 200g, after which the net
voltage remained fairly constant around zero. The inaccuracy could be an indication of
the system sensing dead zone for small masses.
The system experiences a decrease in sensitivity as the load is placed farther away from
sensor, as indicated by the lower voltages recorded at the 55+mm range. This trend is
exaggerated for the higher loads, as seen for 500g & 1000g in both thin & thick paddle
experiments. Smaller loads which remain close to the zero mark have greater linearity
and slope close to zero. Higher loads (500g & 1000g) dip starting at 55mm away from
sensor for both thin & thick paddles. These patterns indicate that some hydraulic pressure
is lost when the tube is compressed farther from the sensor and highlights the importance
of properly constraining the hydraulic chambers to prevent any expansion of open surface
area. Surprisingly the results for the thin paddle were more linear for each load. This
could be from the small flexion in the thin paddle contouring better to the tube surface as
it deformed (Figure 88)
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The loading was fairly consistent for both chambers of testbed 2, performance was
similar to Testbed 1 in displaying erratic behavior for the lower masses. It exhibits
similar accuracy estimates that these masses are close to the sensor system’s dead zone.
The thick paddle stabilized its reading with excellent linearity after 200g like testbed 1
previously. The thin paddle did not stabilize for the same loads and fluctuated even until
420g. The peak uneven measure for testbed 2 is slightly less than testbed 1 but
comparable (Figure 87). Testbed 2 showed good linearity and consistency for the lower
masses, regardless of proximity to the sensor. The 500g and 1000g thin paddle series
show sharp drop offs at the 55mm mark, comparable to the location from testbed 1.
Although the drop for these is steeper than the data for testbed 1 as seen in Figure 90.
Overall the low mass responses for testbed 2 had lower voltage readings than testbed 1,
but for higher loads (like 500g & 1000g) the voltages were higher for averages in loading
location (Table 11).
Error Plot Results:
Table 10 below shows the experimental results for average voltage from load location
compared to predicted values from the linear regression test for % error. The thin paddle
had consistently smaller errors than the thick paddle, indicating generally higher accuracy
despite flexion. The errors were greatest at the smallest loads (under 150g). Higher loads
had considerably smaller average errors even though they drop off. This shows the rate of
error as a function of mass.
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Table 10: Average % error for Testbed 1 load location
The error plot for testbed 2 (Figure 99) exhibits similar patterns for the thin paddle error
to testbed 1. This shape is a sharp drop for loads under 100g then convex dip, with level
settling for higher loads.
Table 11: Average % error for Testbed 2 load location
The thin paddle had consistently smaller errors than the thick paddle for testbed 1. The
errors were greatest for the lowest loads, re-iterating that loads below 100g may not be
within the sensing range (also shown in Figure 89). The error drops sharply after this
mass, and higher loads have consistently smaller average errors. Figure 85 below shows
the rate of error as a function of mass. The thick paddle error is more linear and
predictable after the 200g point, which relates to sensing reliability of the system. The
error for testbed 1 seems to be consistent (and thus more predictable) when loaded with at
least after the 200g. The thin paddle does not reach a level so has a more unstable error.
142
Figure 98: Error values for Testbed 1 for thin & thick paddles.
For testbed 2 the thick paddle initially has a high error as well but drops sharply before
200g, indicating a larger sensing dead zone for the thick paddle. However the greater
linearity shows that the thick paddle has superior accuracy and consistency for masses
above 250g. Error plots for both testbeds clearly indicate that the accuracy of the system
increases with the amount of load and is most inaccurate for loads under 200g.
143
Figure 99: Error values for Testbed 2 for thin & thick paddles.
Testbed Discussion:
Testbed 1 exhibited better performance (lower error values for) low loads than testbed 2.
In both cases the thick paddle had comparable linearity regression to the thin, and in both
cases superior consistency for loading location. This shows that the introduction of
fittings does not significantly degrade the response of the system when compared to the
ideal conditions. This also leads to the conclusion that although a deformable surface may
have better contact with a hand, the thicker handle has more consistent results, especially
for higher loads. The lower forces are also more difficult to detect than the higher loads
(especially with the thicker paddle) so for smaller loads this type of system is more
susceptible to tolerances and tube constraint issues. Both test beds generally showed
reduced response to the weight stimuli as the stimuli was moved further from the sensor
but this reduction in response was more exxagerated at higher forces. This is true of both
144
the thin and the thick padels, although the effect seemed less exagerated for the thick
padels. The smaller exageration in reduced response with the thick padels is positive for
our application because the padel between the user stimuli and the hydraulic chamber
will better mimic the thick padel than the thin one.
This examination also gave insight into the design application for the bike handle.
Original intuitive design had placed the sensor closest to the inside center of the bike
(where the two handles meet.) However examining how a rider applies forces to steer a
bike revealed that turning forces are more effective more t o the outside of the hadlebars
than the inside. Therefor the sensor should be kept at the lateral side for higher consistent
accuracry.
Handle 4V3:
Grip Oscillations from Steady Pedaling:
Oscillating force readings on handles were recorded. Figure 94 displays the revolutions
per minute (rpm) along with the handle forces. RPM for this test was steady averaging 93
rpm which is within range for a healthy recommended cadence (88-95rpm) [27].
The amplitude of the forces could be an indication of asymmetry in the pedaling forces
transmitted through the trunk. Abnormalities in pedaling motion can affect the loading
pattern on the handles.
Examining the curves in Figure 93; the right hand lifts (pulls) up harder and faster than
the left (indicated by the shorter rise time to force peaks), then drops abruptly (250ms)
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and decreases further for a larger downward pushing force. The pattern of the right hand
is 250ms of peak & drop, then 250 ms of slow change in force from pulling to pushing.
The left hand had an equal period to the right, but different shape and division between
these actions. In the left hand each large loading is followed by a second faster loading of
almost equal amplitude. This is a 370 ms primary load & unload action (slower than the
right hand) and a 100ms secondary load & unload action ending with net zero force on
the handle and moving into the ‘pushing’ phase (Figure 94 A & B). Results from studies
in strength pedaling have shown to stabilize trunk postures despite deficits in the lower
extremities [23].
All three trials had loading patterns which differed from left to right, but patterns for left
and patterns for right were consistent between trials for magnitude, and shape, and
period.
Linear Increase in Isokinetic Grip:
This test evaluates the feeling of symmetricity and comfortable loading between two
hands and as an input device for zero to 70% of MCL.
The left hand in Figure 95 had a smoother transition to peak and smoother drop down for
unloading than the right. The right hand had a sharper increase and decrease very close
peak forces. Both curves have a 2.5 second resting period at the end. The unloading
patterns were almost identical for both handles. The dip at the peak force for the right
146
hand could indicate that subject needed to adjust their grip. This coincides with studies
relating comfort and maximum force output from high loading rate [56].
It is important to note that since there is uneven surface area for the two hand surfaces in
contact with the sensing area, some of the force from the higher-loaded lateral side will
be counteracted by the pressure on the smaller medial side.
Steady Symmetrical Pedaling:
The normalized curves for both pedal cycles (1 Hz) are seen in Figure 98. They have
been aligned according to the same zero loading point for pedal TDC (indicated by 330°
CW from TDC). When evaluating the data for pedal forces it is important to consider that
since the pedals are connected rigidly through the crank, any deficits or impairments of a
weaker leg can be overcome by the stronger leg. The higher compression forces from the
right leg may not just be higher strength from the right led but may be attributed to a
deficit in the left leg (also referred to as ‘negative work’) [23].
Maximum compressive forces are comparable for the primary and secondary peaks seen
in Figure 100. Maximum compressive forces took place at 36° & 90° CW from TDC for
the left and right feet, respectively. The right foot exhibits peak compressive forces at the
appropriate rotation angle but the left foot reaches peak compression sooner by almost
30% of the cadence cycle [23, 27]. Peak tensile forces were greater for the left foot than
the right by 5.5 lbs and took place 15% later on in the pedal cycle. The locations of these
peak tensile forces are at 240° & 294° CW from TDC for the right and left feet,
respectively.
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The loading pattern for both feet also displays an unusual secondary rise in compression
at BDC (180°) which differ between each other by 11% magnitude and 4% cadence
timing. As reviewed from section 2.3.3 there is normally no such increase in force,
simply a small drop in compressive loading at the BDC. This pattern could possibly be
attributed to the stick-friction from the stationary bike when the normal forces drop to
zero and tangential forces are close to zero.
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4.7 Conclusions & Future Work
Handle System:
The experimental results obtained were successful in demonstrating that a hydraulic
pressure sensor can be used to measure a patient’s applied force and therefore their
intended turn as a haptic interface to a virtual environment. Two testbeds and three
prototypes were built to test the feasibility of the use of this type of sensor, and then to
test the use of the sensor as an input device in the design application. The sensor system
has the potential for excellent linearity & response and gave insight into the
improvements necessary for future final design and software model. This is a successful
first phase for proof of concept but the prototype system needs further characterization.
The handle tests assumed that forces were applied evenly across the chambers, a series of
paddle tests should be conducted with 4V3 prototype. The differences in surface area
from hand anthropometry will yield different pressure values for each loading scenario
and should be further investigated. The system hysteresis needs to be examined for load-
to-unload performance, as well as response time for dynamic loading.
The handle system needs further ergonomic evaluation and study. A hand- contoured
ergonomic surface for grasping could improve effectiveness of tubing. A double-frustum
implementation could be more comfortable. Opportunities for patient-specific surfaces
from 3D scanning exist also. Integration of heart monitoring should be reinvestigated to
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consolidate the number of hardware attachments needed. Haptic feedback could be
expanded to be included in the handles.
Implementation of a valve system for easy fill and evacuation of trapped air would need
to be examined. The overall size of the system could be decreased by implementing a
manifold system for each hydraulic chamber rather than using the current ‘coil’ pattern.
This would also require validation and testing.
Pedal System:
The pedal system successfully monitored kinetic and kinematic parameters of the rider’s
lower extremities. Further evaluation within a range of stationary bikes is necessary to
observe any unique loading patterns in the pedal forces, as observed in the steady-state
pedaling test. The pedal system needs electronic hardware to be made wireless and
possible alternatives to the accelerometer for tilt need to be tested. Modifications are also
necessary for the interaction with the load cell to decrease lateral tipping and improve
perpendicular alignment with the foot plate.
An infrared system attached to the pedals can simplify the system and provide a more
reliable way to calculate the instantaneous pedal tilt and revolutions per minute. The IR
solution has 2 components: reflectors that are placed on the pedals and IR receivers that
are setup in line of sight of the pedals. Three reflectors would be placed on each pedal
along the side edge of the footplate, crossing th axis of rotation. One reflector would be
located on this axis, one on the front edge, and one at the back edge. The IR system
150
emits light from the receiving locations and records the amount of time before the light is
reflected off from the pedals and return to the receiver. The timing could be used to
determine rpm and pedal tilt at any pedal position.
To reduce the size of the system and improve integration, a custom pedal raceway needs
to be designed rather than fabricating and assembling around an off-the-shelf solution.
An alternative sensing solution for pedal position, velocity, and tilt uses three rotary
string potentiometers to track the center of both pedals and their front edges. Figure 1
shows profile views of both pedals and their trajectories during pedaling (red dotted line).
On one side (left for ex.) there is a static rotary string potentiometer fixed to the center of
the pedal’s axis of rotation (block B), and one attached to the front end of the pedal
(block A). The difference between the two points would yield the pedal’s angle of tilt,
and the difference of the center potentiometer from the starting point would indicate
position (and velocity using a time derivative). On the opposite pedal, the center of
rotation is a known position because it is offset exactly 180° from the left pedal center of
rotation. Therefore the right pedal requires only one potentiometer (block C) for
comparing its value to the value 180° opposite block B.
Figure 100: Position, velocity, and tilt sensing using 3 rotary string potentiometers
151
Bike Overall System:
There are several improvement possibilities for the complete bike system. To monitor
trunk rotation and lean of the user the seat would be instrumented with pressure sensing
hardware. The pressure sensors used in the handle system could be potentially modified
for this application.
Integrating wireless signal transmission would ease installation and increase robust
handling by eliminating the delicate cables and connections currently implemented.
Haptic feedback hardware should be further investigated to increase the user’s immersion
with the virtual environment. In addition, stimulation of each sense needs to further
investigated:
• Tactile: wind, vibration, road texture • Auditory: more diverse realistic natural sounds and auditory response of virtual
bike components • Visual: expanded environments, diverse and custom avatar creation via 3D
scanning, integration of patient’s actual neighborhood as simulated route
This first prototype of the bike system was successful in demonstrating that a modular kit
can monitor and record kinetic & kinematic parameters of the rider. Comparable systems
can be extremely expensive and necessitate purchase of a completely new system rather
than being offered the flexibility to enhance the functionality of their existing system.
This type of device creates possibilities for clinicians to diversify their treatment by
prescribing a patient to outfit their home equipment to assist and communicate their
progress in a tele-medicine context.
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5.0 CONCLUSION
Two examples have been presented of medical mechatronic devices for assisting patients
with quantifiable evidence-based rehabilitation. Current rapid prototyping (RP)
technology allows for single step manufacturing of complex objects with embedded
electronics and is currently being implemented in all major fields of medicine. When
combined with non-invasive 3D scanning techniques it allows clinical assessment and
treatment in a telemedicine context regardless of geographical borders.
This work has presented a process to combine state of the art 3D scanning hardware and
software technologies for human surface anatomy with advanced rapid prototyping
techniques so that novel custom made orthoses and rehabilitation devices are rapidly
produced and ready to be used by patients. It has also presented a modular exercise
bicycle kit for clinical or home-based tele-rehabilitation, which was designed
emphasizing RP capabilities.
The unique benefits of RP tools and processes have the capacity to partner intelligent
medical devices to a specific patient & application via mass-customization. Modular,
inexpensive rehabilitation devices such as these open possibilities for clinicians to
diversify their treatment hardware in-house or prescribe a patient to outfit their home
with the equipment to record, convey, and assess their improvements remotely.
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154
deform the desired shape
Pour Bust of Leg:
The open edge of the cast is filled and plaster is
poured into the leg cavity. Curing time is
approximately 20 minutes.
Form Manipulation:
• Timeline for Form Manipulation: • Surface Bust Modifications: 45 minutes (for an experienced technician) • Drying Time: 15 mins • Shaving & Smoothing Surface: 15 mins • 1.5 to 2 h total
Regardless of the type of AFO (PLS, semi, or full coverage) being created, sculpting
operations for a subject’s anatomy will be dictated by the gait analysis and biomechanics
assessment.
Remove Cast:
The cast is cut off from
the bust. The ink
markings from the
original sock have now
been transferred to the
surface of the bust.
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Examine Markings:
During casting, the markings on the sock can slide along the surface
up to ½” away. The technician scrutinizes the transfer markings and
compares their locations to the work order before darkening
(confirming) them. This requires the technician to have some
fundamental anatomical and kinematic gait understanding.
Problems which can occur during casting are:
bubbles, wrinkles, chips, deformation resulting
from premature removal of cast from patient.
File Off Toe:
The excess material at the end of
the toe is ground down by hand
until the bottom surface is flat.
To determine how much and
where to wedge out the foot, the
markings are compared with the
work order description such as
“drop 1st ray” or “drop 5th ray”
Evaluate Perpendicularity
Throughout the manipulation phase it
is important that the leg be
perpendicular to the foot. The bottom
surface of the foot is ground down
using visual confirmation.
For patient pronating or supinating, an
intrinsic heel wedge can be carved out or
added. Regardless of subject’s AFO
correction type, the bottom surface is kept
flat.
Pump Bump usually occurs on the lateral
side of the heel and needs to be sculpted
outwards.
156
Landmark Skin Layer:
The surface of the skin is
marked to provide a
reference datum for later
when surfaces will be
ground down.
Mark Cutoff Height:
The top edge for
locating the rope is
marked.
Attach Roping Contour Guide:
Once complete there should be a total ½” side to
side spread across the top of the AFO
There is a 5/16” Distance from the top of the
rope to the beginning of fillet.
Staple Buildups:
Regions to be contoured on the leg are
stapled. Using 1/8”offset normal to
surface, the cuboid, 1st metatarsal, and
5th metatarsal are marked.
Note the 1st & 5th metatarsal on either
side are key for whether the foot is
loose or firm in the orthotic.
The navicular is
marked as a dome
shape with 1/8”
rise normal at its
tallest point.
Heel:
Stapled are added along the heel curve
1/8” offset normal to surface.
The Lateral Meticulus surface is also
expanded outwards by 3/16”. The exact
location of this feature can vary from
patient to patient lifestyle.
157
Plaster Additive Surfaces:
Starting at the heel, the surface is built outwards
using the staples as surface markers. It is more
important the surface the bony prominences of the
ankle than the fleshy surfaces since the latter
conforms easier.
Flat Surface:
In case the bottom of the foot is not flat, additional
plaster is allowed to set underneath. In case a
sustentacular lift is required to raise the arch it would
be sculpted at this stage.
Smoothing Surfaces I:
15 minutes pass for the plaster to dry. The additive
surfaces are hand filed down to the tope of the
staples, whilst the perimeter is filed down until the
skin surface marker is visible. The surface is filed in
a motion using the vertical grain of the leg.
Smoothing Surfaces II:
Water and soap are used to finish the bust surface. The
final checks are for smooth, gradual surface with no
staples showing and no sharp ridges which can impede
the vacuum forming.
Any small pockets (less than 1/16” diameter) are filled in
with putty.
158
Fabrication:
Once the corrective surfacing operations have been performed on the leg bust, the
fabrication of the AFO begins
Vacuum Forming:
A stocking is fit over the leg bust and acts as
a wick to draw air out. The pre-heated 3/16”
polypropylene sheet is placed on the bust
starting at the heel. The vacuum operation
takes approx 30 seconds to be formed around
the leg and requires two people.
Cut Out Orthotic:
Hand marks outline the cut contour for the
AFO, this stage separates the different
variations and types of orthotics. This cutting
stage also leaves an uneven ¼” gash in the
leg bust after cutting.
Edges:
Edges are ground down & smoothed. The
back vertical surface is loaded and bent
forward to check for even splay during
weight bearing.
The red line indicates the ½” total lateral
spread for freedom of motion.
159
Form Storage:
Modifications:
In case surface modifications are required after the
initial fitting, the orthotic is clamped in the new
position, heated to a semi-pliable state and allowed to
cool. Edges can also be ground down or filed.
Storage:
The average AFO life is 12-18 months before insurance
will pay for a new version, however the physical
modified leg bust is only stored for 2-3 months due to
physical space constraints.
160
APPENDIX B: RP Materials Detailed Comparison
Table B1: SLS Material Properties
Table B1: SLA Material Properties
Table B1: FDM Material Properties
161
Flexural Properties:
SLA is generally more brittle than other RP methods here, but has ranges of materials
which can almost imitate thermoplastics like polypropylene, polyethylene, ABS.
Figure 101: SLA material flexural properties range
Figure 102: FDM material flexural properties range
162
Figure 103: SLS material flexural properties range
Tensile Properties:
Figure 104: SLA material tensile properties range
163
Figure 105: FDM material tensile properties range
Figure 106: SLS material tensile properties range
164
APPENDIX C: Genex Facecam 3D Scan Accuracy
165
APPEENDIX DD: Cha
pter 4.00 Bill off Materrials
166
167
APPENDIX E: Adjustable Ramp for Incline Gait Analysis
Figure 107: Recessed and elevated states of adjustable incline gait ramp
This project was completed with the ongoing support and guidance of the Motion
Analysis Laboratory, Spaulding Rehabilitation Hospital, Boston, MA. The author would
like to express their appreciation as well to William Cusack for his assistance with the
biomechanics and design.
E.1 Device Overview
In order to study healthy and pathological gait at varying slopes, an adjustable
instrumented gait ramp was designed and implemented around an existing embedded
level gait walkway.
The principal limitation of the existing setup (MAL, Spaulding Rehabilitation Hospital,
Boston, MA, USA) was that it was only possible to study level walking. During an
everyday routine outside of clinical setting, a patient may experience varying terrains
including, (but not limited to) stairs and sloped walking surfaces. It has been previously
demonstrated that when transitioning from walking on level to sloped surfaces there are
changes in neural control strategies [10], motor coordination [80], and trajectory planning
168
[8]. As a result, varying the slope of the walking surface affects muscle activation [9],
power [11], and thus, the dynamics of the lower limbs [81]. An adjustable, stable system
was required to fulfill the following criteria:
• Continuous rigid incline surface for gait analysis
• Adjustable to 3 angles (2.9, 5.7, 8.5 deg, i.e. 5%, 10%, 15%)
• Do not interfere with motion capture reflective marker line-of-sight
• Additions fit in existing working envelope
• Rigid connection for force plates
• Minimal distinction from original system
• Minimal distinction between force sensing plates and walkway
A hydraulic scissor lift provides the vertical actuation at the upper end of the ramp while
a caster wheel assembly allows for a degree of freedom at the lower end. Along the frame
of the ramp, eight compressed air pistons assist by supporting a portion of the system’s
weight as well as providing damping of structural vibrations during gait. A pair of
mechanical stops provides a hard safety and minimizes deformation. When retracted the
ramp rests seamlessly within the existing walkway to preserve the original function of the
laboratory.
E.2 Incline Gait Analysis Systems
Biomechanics research for incline & stair ambulation has necessitated design and
implementation of a range of laboratory devices to facilitate capture of kinetic and
kinematic parameters. Prentice et al. studied gait transitions using a 3m adjustable incline
ramp between 2 horizontal platforms [8]. This is comparable to the ramp used by Kuster
169
et al which supported a rigid scaffold 2m up the surface with a flush aluminum plate 1cm
thick, bolted to the 4 corners of the load cell below [11].
Lay et al conducted extensive testing for forwards and backwards incline gait using an
adjustable gait ramp. This is a 3.11m long frame constructed from rigid aluminum,
covered with a plywood walkway, and connected with a pin joint at one end to a
hydraulic scissor lift. An embedded force plate was centered and stabilized from below
with incline-specific vertical struts[10].
E.3 Design & Sub-Assemblies
The following section describes the key subassemblies for the ramp design. Safety of the patient and existing laboratory equipment were the highest priorities when
designing the new system. The walkway itself must be rigid to limit unwanted resonance
transferred to the floor which can affect the measurements from the load cells. Patients
expected to use the system may already have gait deficits making their stances unstable.
Whilst walking along the incline this could cause them to become uncomfortable and
nervous if they do not feel secure from flex in the walkway. A steel structure supports a
plywood walkway surface, actuated by hydraulic pistons with mechanical stops as safety
backup measures, and pneumatic gas springs to counter the weight of the walkway during
lifting and at the same time damp residual vibrations.
170
Figure 108: Ramp Subassemblies
A: Hydraulic Scissor Lift and Adapter Plate B: Hinge Assembly C: Mechanical Safety Stop Assembly (x2) D: Gas Spring Assembly (x8) E: Force Transfer Pads (x2) F: Structural Walkway G: Caster Wheel Assembly Structural Walkway (F) The incline structural walkway is a welded & cold-fastened steel frame supporting a .5”
(12.7mm) pine wood walking surface to minimize weight and vibration. This surface has
also been tiled to blend in with the surrounding floor area. Two primary 12’ (3.66m) steel
S-beams run the length of the incline structure which supports five steel I-beams cold-
fastened crossways in between (Figure 109). Around the perimeter of both force pads are
four steel angle iron braces to minimize deformations immediately adjacent to the force
pad edges.
171
Figure 109: Structural Walkway Frame Detail
Gas Spring Assemblies (D) Gas springs were installed as a means for distributed load support & vibration damping,
selected for their compact size and reliability. The springs consist of two concentric
cylinders with filled chamber of nitrogen gas which becomes compressed when the
walkway is in resting mode. These were mounted in the recesses between the steel
crossbeams to maximize their effective stroke (Figure 110) and when fully compressed
clear the frame and floor (Figure 111). The lower ends of the springs are attached to the
concrete floor with anchor plates and expanding lag bolts.
172
Figure 110: Gas Spring Detail
Figure 111: Gas Springs in Fully Compressed State between the cross-beams Each selected stroke length was dictated by the maximum and minimum hypotenuse of
the cavities underneath the beams, considering margin remaining at both compressed and
extended conditions and maximum vertical force component available for lifting the
ramp structure.
Figure 112: Clearances for Expanded and Compressed Gas Springs
173
A moment balance about the pivot point for the casters was used to equate the gas spring
force capacities with the weight of the ramp at each inclination (5, 10, 15%).
Figure 113: Reaction Normal Forces and Center of Mass
One equation per crossbeam was prepared and the torques were summed for the level and
incline settings. The number and capacity of gas springs were optimized to negate the
weight of the ramp as evenly as possible.
Figure 114: Force Convention for Gas Springs
From Figure 114, the following spring quantities and capacities were implemented to
balance the net moment about the caster wheels (Figure 115).
F1 = 2 x 200lb springs F2 = 2 x 50lb springs F3 = 2 x 25lb springs F4 = 2 x 25lb springs
174
The gas spring assignments were included for the analytical calculations resulting in net
moment about the caster for each incline.
Figure 115: Net Force vs Inclination for Hinge Barrel
In Figure 115 above the calculated net force for the ramp on the hinge is graphed. This is
derived from the net moment balance about the caster for each of the three inclines. At
the lowest inclination for level walking, the 1151N force on the hinge is negated by the
pads on which the ramp rests. The load on the hinge is initially 551N since the gas
springs are oriented almost horizontally and have a very small vertical force
component15. The net force zero point is at 8.03% incline (16.06°).
Mechanical Safety Stops (C) As a safety precaution is was necessary to implement mechanical hard stops for the three
incline settings for the walkway. The stops decrease vertical deflection, greatly improve
lateral rigidity for the walkway and eliminate loading on the hinge joint. For each stop
assembly a pair of slotted steel tubes pivots between the floor anchor points and the steel
15 This force corresponds to the 2.9° inclination
175
frame underside of the walkway. These capture a specific pair of steel tube rods for each
inclination.
Figure 116: Mechanical Safety Stop Raised & Recessed Configurations
The stops were mounted in front of the gas springs to remove loading from the hinge
whilst not interfering with the springs damping effects for the lower 84% of the walkway
surface. This location provided the optimal balance between horizontal and vertical
support for the reaction forces during gait. When not in use the tube sections rest end to
end in the forward cavity as seen in Figure 116.
176
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