Instrumenting an abstract object

7/30/2019 Instrumenting an abstract object

1/46

Instrumenting an abstract object

Group Design Project : Group 29

Team : Alexandros Nikolaou

Christopher Long Chung Pang

Hamish Dalrymple

Nikhil Banerjee


2/46

Southampton Hand Assessment Procedure The Southampton Hand Assessment Procedure (SHAP) is a simple measure

of hand functionality.

Originally developed to assess the effectiveness of upper limb prostheses,

the SHAP has now been applied to assessment of musculoskeletal andneurological conditions.

Used in conjunction with other tools, it can observe the function of the

entire limb


3/46

SHAP SHAP can be used to monitor progress and compare performance. This is

a clinically validated hand function test.

The SHAP is made up of 8 abstract objectsand 14 Activities of Daily Living (ADL). Eachtask is timed by the participant, so there isno interference or reliability on the reactiontimes of the observer or clinician.


4/46

Project proposal The basic aim of this project is to aid SHAP in achieving more detailed

results, helping with its overall assessment

We aim to provide a wireless instrumentation module for one of the

abstract objects (sphere) in the SHAP tests

Information related to the motion of the sphere in 3D space subjected by

the user will be transmitted wirelessly to an external data logger

This data will ensure a more detailed analysis of the users limb

effectiveness and will further aid the assessment of the users recovery

USER

TASK

SENSOR

MODULE

WIRELESS

TRANSMISSION

DATA

LOGGER


5/46

Understanding the engineering problem The object is under motion in three dimensions :

6 Degrees of Freedom which need to be measured

Inertial Measurement Unit Gyro Free : Due to large

inaccuracies in gyros in instrumenting small objects

accelerometers will be used in a predefined arrangement

Wireless adaptor for communication outside the device

Power: Maintaining enough power for sensors and wireless transmitter keeping

in mind space constraints Robustness : Keeping the components secure inside the object while it is

manipulated by the user

Size: Module must be small enough to fit in the given abstract object


6/46

Visualization

Diameter = 72mm

Microprocessor

Wireless Transmitter

Data

Logger

Accelerometers


7/46

GF-IMU : Gyro free - Inertial Measurement Unit The object under observation has 6 degrees of freedom which will be

measured using accelerometers alone (gyro free)

We aim to establish an optimal number and geometrical arrangement of the

accelerometers

The purpose is to achieve a good measure of accuracy and observability of

the linear and angular accelerations


8/46

Accelerometer arrangement Mechanization equations: Differential equations describing the position,

velocity and attitude as functions of the sensor outputs

They depend on the physical configuration of the sensors relative to both

the object body and the reference frame

Strapdown Mechanization : Sensors are strapped onto the body frame

Advantage: Decrease in size and weight

Disadvantage: Computational complexity


9/46

Geometrical Arrangement Tetrahedron

Reasoning:

No. of

Acceleromet

ers

2 4 6 8

No. of Wires

required

6 12 18 24


10/46

2D analysis of the equations Assuming we are using two-axis accelerometers Let the readings be y1, y2, etc.

For a static object, the readings will be

y1 = y3= y5 = 0

y2 = y4 = y6 =g

2

1

6 4

5 3

g


11/46

2D analysis of the equations The readings arey1 = y3

= y5 = g sin

y2 = y4 = y6 =g cos

2

1

6

5

4

3

g


12/46

2D analysis of the equations While in linear motiony1 = y3

= y5 = g sin + a cos

y2 = y4 = y6 =g cos + a sin

This set of equations can be solved numerically

2

1

6

5

4

3

a

g


13/46


14/46

2D analysis of the equations Radial acceleration (towards the centre of rotation) Tangential acceleration

= 2 =

2

1

6

5

4

3

g


15/46

General equation From Hanson

Combining linear and angular accelerations

= +

1

21

2

+

1


16/46

General equation

= +1

21

2

+1

y is the vector of the readings from the accelerometersy = (y1; y2; ...; yN)

is the vector of unknowns, i.e. the angular and linear accelerations in the

x, y, z axes.

H is the regressor matrix

=1 1

1


17/46

The regressor matrix Used to solve the equation

Also provides a condition number

= 1

The condition number measures the worst case of how much accuracy

would be lost due to small changes in the data received


18/46


19/46

HardwareParameters

System Physics behind

Scale

Ease of use Other parameters


20/46


21/46

Wireless Data Transmission Requirements

12 channels without processor

6 channels with processor

Low power consumption

Small size

Short range

Ease of use

Cost


22/46

Wireless Data Transmission Easyradio ER900TS transmitter

31x12x4 (mm)^3

3.3V

82.5mW

14.56 GBP low cost

Data Encryption 16-bit


23/46

Wireless Data Transmission Easyradio ER900RS receiver

Pair with ER900TS transmitter

23.81 GBP


24/46

Main PCB - Processor Requirements

6 inputs/outputs

Small size


High processing speed not required


25/46

Main PCB - Processor Arduino Pro mini 328

3.3V

3.3x1.8x0.8 (mm)^3

8 MHz processing speed

13.22 GBP


USB connection using adaptor


26/46

Power Supply Requirements

Small size

High endurance

Lightweight

Rechargeable

Low cost


27/46


28/46

Hardware Accelerometers

Requirements

> 1kHz Bandwidth

Measuring range ~ +/- 6g


Considerations

Type of chip mounting

Design a PCB?

Size of complete package

Synchronization


29/46

Hardware Accelerometer

Suitable device found:

Triple Axis Accelerometer ADXL345

Measurement range: +/- 2, 4, 8 & 16 available

Output data as 16-bit twos

SPI (3 or 4 wire) digital interface

3.2 kHz Bandwidth

PCB dimensions: 15.5 x 22 mm


30/46

CAD Design Rapid Prototyping Machine


31/46

CAD Design Design Constraints

Cost of material

Size Required

Geometry of Accelerometers


32/46

CAD Design Design Considerations

Accessibility of the components?

Access to sphere after construction?

Design so far:


33/46

Accelerometers

Easy Radio

Microprocessor


34/46

Battery


35/46


36/46

Programming, Data extraction and DataProcessing


37/46


38/46

Data Extraction : Communication modes Data Extraction from the ADXL

Two communication modes : SPI and I2C

I2C communication drawback :

X Hard coded I2C address, same for all accelerometers

X Cannot address accelerometers individually

SPI Communication chosen :

No addressing required on bus while communication

Communication is faster

No delays between inflow and outflow of data


39/46

SPI communication

4 wire communication

For selecting accelerometer: SS slave select wire LOW

Digital output pins served this purpose on the master device i.e. Arduino Pro

Mini
http://upload.wikimedia.org/wikipedia/commons/e/ed/SPI_single_slave.svg


40/46

Accelerometer ConfigurationRequirements:

Continuous 3 axis readings for acceleration


5 g range for acceleration

Register values in ADXL345 were set as per requirements

The decided rate was 1600 Hz with bandwidth 800 Hz (minimum 90A current),thus we use the rate code 1110 for this register.


41/46

Program Structure Setup :

o SPI communication mode, rate, digital SS pins

o Serial communication rate

o Initialize velocity displacement variables

o Configure accelerometers g-range, data rate, etc

Loop


42/46

Data flow


43/46

Testing

Static Test

Use Horizontal and vertical rotary table


44/46

Testing

Motion Test

Use gravity and standard equations

(v=u+at ect)

Use Robot arm


45/46

Gantt Chart


46/46

Future Work

Circuit design

Connections

Built of outer cell using rapid prototype machine

Data transmission

Software for computation

Testing

Documents

Instrumenting an abstract object