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Delft University of Technology
Faculty of Mechanical, Maritime and Materials Engineering
Department of Biomechanical Engineering
MSc Thesis: Investigating head-neck stabilization using combined mechanical
and galvanic vestibular stimuli
Anoek M. Geers
November 6, 2012
Supervisors:
Ir. Patrick. A. Forbes
Dr. Ir. Riender Happee
Dr. Ir. Alfred. C. Schouten
ii
Information
Title:
Investigating head-neck stabilization using combined mechanical and vestibular stimuli
Type of report:
Master of Science Thesis
Author:
Anoek M. Geers
Student Number:
1304976
Institute:
Delft University of Technology
Faculty of Mechanical, Maritime and Materials Engineering
Department of Biomechanical Engineering
Master Biomedical Engineering
Board of Examiners:
Prof. Dr. F.C.T. van der Helm (3mE, BMechE)
Dr. Ir. R. Happee (3mE, BMechE)
Dr. Ir. A.C. Schouten (3mE, BMechE)
Dr. Ir. H. Damveld (AE, Control & Simulation)
Ir. P. A. Forbes (3mE, BMechE)
iii
Abstract
In studying the head-neck system, head dynamics are often regarded as being linear and time invariant within
experimental conditions while nonlinearities are explored across different conditions. The goal of this study
was to assess if the superposition principle is valid in head-neck stabilization during combined torso
perturbations and continuous galvanic vestibular stimulation (GVS). Additionally, the aim was to identify ideal
perturbations and it was hypothesized that direction (torso) and amplitude (torso and GVS) of the inputs affect
the ability to sufficiently identify system dynamics. Nine seated subjects were perturbed in lateral direction on
a motion platform while GVS was simultaneously applied. Along with simultaneous perturbations, isolated
perturbations were performed. Both the mechanical and galvanic input signals consisted of multisine signals
and were designed to be mathematically uncorrelated. For the motion perturbations, two variations were
included of both direction (translation and rotation) and amplitude (100% and 200%), while there was a fixed
bandwidth and frequency distribution (0.119-4.167 Hz, nine frequencies). The GVS signal was applied in a
bilateral bipolar configuration at 4 mA and had a fixed bandwidth as well (0.179-4.107 Hz, six frequencies).
During trials subjects had their eyes closed and were asked to perform a natural stabilization task.
Displacements of the head, torso and platform were recorded using a motion capture system. System
identification techniques were used to identify the relationship between respectively inputs GVS and torso
motion and output head motion. Results show that it is feasible to apply low-level torso perturbations together
with continuous galvanic stimulation in studying the head-neck system as high coherencies and consistent
behavior are found for the transfer functions from mechanical and galvanic inputs to head motion over all
subjects. Responses to isolated perturbations showed results very similar to literature, showing system
behavior close to linear. Modulations due to amplitude were attributed to nonlinearities such as sensory
thresholds as implemented mechanical perturbations were small. It is concluded that superposition principle
does not hold in sensory integration as gain, phase and coherence modulations were found with the addition of
GVS.
Keywords: galvanic vestibular stimulation, mechanical torso perturbations, head stabilization, sensory
integration, vestibular contribution, superposition principle, system identification
iv
Table of Contents
1. Introduction .................................................................................................................................................... 1
2. Methods .......................................................................................................................................................... 2
3. Results ............................................................................................................................................................. 7
4. Discussion ...................................................................................................................................................... 19
5. Conclusion ..................................................................................................................................................... 21
6. References..................................................................................................................................................... 22
Appendix A: Statistical tables
Appendix B: EMG measurements and analysis
1
1. Introduction
Reflex control of the neck is exerted primarily by the vestibular system and the proprioceptors in the cervical
spine (Keshner 2009) together with visual feedback mechanisms. However, the exact contribution of each
sensor during functional motion remains uncertain. Being able to make a systematic disassociation between
the different contributors in head-neck stabilization is particularly important to help investigate head-neck
neurological disorders which affect control and for which stabilization is a critical issue. In previous research,
the head-neck system dynamics have been studied by applying mechanical perturbations to the torso with the
head free to move (Keshner, Cromwell et al. 1995; Keshner 2003). During relatively small perturbations
dynamics are often regarded as being linear and time invariant within fixed conditions while nonlinearities are
explored across experimental conditions (Forbes, de Bruijn et al. 2012). The effect of applying independent
stimuli simultaneously and their adherence to the superposition principle has received little attention even
though humans are constantly exposed to multiple stimuli during daily head-neck stabilization behavior. The
goal of this study is to assess the validity of the superposition principle in head-neck stabilization during
combined lateral torso perturbations and continuous galvanic vestibular stimulation in eyes-closed conditions,
in an effort to identify sensory nonlinearities within the system.
Galvanic vestibular stimulation (GVS) has repeatedly been used as an isolated stimulation of the vestibular
organ, providing insight in the vestibular contributions to posture control (Fitzpatrick, Burke et al. 1996; Dakin,
Luu et al. 2009; Day, Marsden et al. 2010) and has been successfully applied to study the head-neck system
(Ehtemam, Forbes et al. 2012). Small electric currents (below 10 mA in general) applied through surface
electrodes directly stimulate the vestibular afferents, thereby altering the firing rate and resulting in a
compensatory postural response. GVS is a non-physiological stimulus inducing relatively small movements (2-3
deg/s2 of head acceleration per mA) and it has the same frequency modulating effect on the vestibular neurons
as natural motion (Day and Fitzpatrick 2005). On its own GVS, has an approximately linear relationship between
the amplitude of the current and the amount of evoked body sway (Hajos and Kirchner 1984). However, when
combined with mechanical perturbations, it has been suggested that there is a nonlinear interaction between
the vestibular signals induced by continuous GVS and platform motion (Inglis, Shupert et al. 1995; Hlavacka,
Shupert et al. 1999). This contradicts sensory integration research which demonstrates the independence of
transient GVS and continuous mechanical stimuli when designed to be mathematically uncorrelated (Cencairini
and Peterka 2006), where the superposition principle as described in Bendat and Piersol (2010) was assumed.
In the present study the hypothesis is tested that similar to Cencairini and Peterka (2006) the superposition
principle holds during simultaneous torso perturbations and continuous galvanic vestibular stimulation in head-
neck stabilization. Differences observed between conditions would point towards nonlinear effects due to
either the characteristics of the physiological mechanisms involved or interference of the two stimuli. The
former would be reflected as differences in the transfer function gain and phase while the latter would be
indicated by differences in coherence without variation in the transfer function. Dynamic system behavior was
assessed during different lateral motion inputs (rotational and translational) applied simultaneously with
galvanic vestibular stimulation with the inputs being mathematically uncorrelated in their frequency content.
As an additional objective, we aimed to identify ideal mechanical torso perturbations and galvanic vestibular
stimuli in such a way that the responses to both stimuli provided significant coherence estimates. It was
hypothesized that the direction of motion (torso) and amplitude (torso and galvanic) will affect the ability to
sufficiently identify system dynamics during simultaneous perturbation and that the amplitude of the torso
motion is a determining factor in the ability to provide coherent GVS transfer functions.
2
2. Methods
Subjects Nine healthy subjects (5 male) with a mean age of 25 (± 2) years and no self-reported history of vestibular or
neck disorders participated in this experiment. Prior to the experiment the testing procedures were explained
to all participants and their written informed consent was obtained. The research was in accordance with the
Declaration of Helsinki and approved by the Human Research Ethics Committee of Delft University of
Technology. In this report data is presented for seven (4 male) subjects, as one subject displayed substantial
voluntary behavior in all trials differing considerably from other subjects, and another was unable to complete
the entire experiment due to nausea during GVS trials.
Apparatus Lateral motion perturbations (0.119-4.167 Hz) were applied using a 6 degree of freedom (DOF) motion
platform. Subjects were seated on a rigid chair mounted to the platform, and restrained using a five point
seatbelt and rigid plates mounted at the left and right side of the chair (Figure 1B). The platform was position
controlled through a real-time computer control system (dSpace, Paderborn, Germany) using custom-made
software (MATLAB, Mathworks Inc., Natick, MA, USA). The perturbations applied in this experiment did not
exceed the common workplace safety limits as specified by ISO 2631-1 (Mechanical vibration and shock –
Evaluation of human exposure to whole body vibration).
Galvanic vestibular stimulation (0.178-4.107 Hz) was delivered using a modified STMISOL stimulator developed
by Biopac Systems, Inc. (California, United States), rated safe for human application, following the guidelines
specified by IEC-601-2-10. The analog input signal was generated offline using a custom MATLAB script and
delivered via the control computer. The stimulating current was applied to the subjects using customized
rubber electrodes coated with Spectra 360 electrode gel (Parker Laboratories, Fairfield, New Jersey). The
stimulation was applied in a bipolar binaural configuration which induced a sensation of roll and yaw rotation
of the head (Fitzpatrick and Day 2004). Electrodes were placed on the left and right mastoid processes and
fixed in place using adhesive tape, a flexible head wrap and/or a swimming cap.
Data collection Using a motion capture system consisting of six Oqus cameras (Qualisys AB, Gothenburg, Sweden), three-
dimensional kinematic data of the head, trunk and platform was recorded at 200 Hz. To monitor head motion,
subjects were asked to wear a tightly secured plastic helmet which had four markers attached respectively on
the front, side, back and top of the head. The mass of the helmet (180 g) was considered to be negligible
compared to the mass of an average human head (~4.5 kg), (Yoganandan, Pintar et al. 2009). Another two
markers were attached directly to the head, at the bottom of the eye socket and in front of the ear in line with
the tragion. To monitor torso motion, six markers were used: three markers on the sternum (top, middle, and
bottom), two markers bilaterally on the acromion and one marker at the spinous process of T1. Platform
motion was measured to confirm torso movement followed chair (platform) movement, by using five markers
attached to the chair: two on the seat base, two on the seat back and one at the backside of the chair (Figure
1A). Additionally, EMG of eight superficial neck muscles was recorded using bipolar microelectrodes and TMSi
Porti EMG system (TMSi, Enschede, The Netherlands). See Appendix B: EMG measurements and analysis for
further details.
Procedures Before the experiment started, subjects were informed about the nature of GVS and a trial stimulation was
performed to familiarize the subjects with the stimulus. During the experiment the subjects were seated
upright on the chair with their feet placed in front of them. Both the chair and constraining supports were
adjusted to each subject, ensuring that the subject was secured as tightly as possible. Stiff foam was pressed
around the shoulders and at the pelvis, and empty spaces were filled with additional foam.
3
Figure 1: Experimental setup. A) Side view of motion platform including passive markers on chair. B) Subject seated on chair, restrained by seat belt and side plates, with passive markers on head and torso. Included is also the head local coordinate system and the positive directions in translation (x,y,z) and rotation (roll, pitch, yaw).
During all trials subjects were instructed to close their eyes (in order to eliminate visual feedback) and to keep
their head upright while staying relaxed, performing a natural stabilization task. Subjects listened to an
informative podcast to distract them from the perturbations, thereby minimizing voluntary responses. To
prevent fatigue, subjects were free to take a break between each trial for as long as was required.
The conditions tested included mechanical only (four), galvanic only (one), simultaneous galvanic and
mechanical (four) perturbations, and no perturbations (one) to measure natural head sway. Each condition had
two repetitions with the exception of the natural head sway condition (to limit experimental time), resulting in
a total of nineteen trials. Each trial had a length of 86 seconds which resulted in a total experimental time of
approximately two hours. The nineteen trials were presented in a random order. All galvanic trials used the
same GVS signal, while four different lateral motion perturbations were applied varying in amplitude (100% -
A1 and 200% - A2) and direction (lateral translation – T and roll rotation - R). Roll perturbations were delivered
with the center of rotation perpendicular to the interaural axis in the middle of the head of the subject. The
center of rotation was estimated for each subject using the motion capture system. Table 1 shows the test
matrix of the experiment, including the ten different conditions.
Table 1: Test matrix for the ten different experimental conditions. Direction: T/R, Amplitude: A1/A2. GVS: 0/1 (on/off)
Stimuli Multisine signals were used for both the mechanical perturbations and the GVS signal. Compared to other
(pseudo)random stimuli such as white noise, multisines have a better signal to noise ratio (SNR), avoid aliasing
and spectral leakage and provide design flexibility in which frequencies are perturbed (Pintelon and Schoukens
2001). Since the sines in the multisine have random phases, the total signal still appears random and is
therefore more unpredictable to the user which helps to minimize voluntary actions. Additionally, Ehtemam,
Forbes et al. (2012) have shown that a multisine can be successfully applied as a galvanic stimulus in the
isolated head-neck system. Selection of the stimulated frequency points was performed using the guidelines of
Translation Rotation No motion
No GVS T-A1-0 R-A1-0 M-00-0 T-A2-0 R-A2-0
GVS T-A1-1 R-A1-1 M-00-1 T-A2-1 R-A2-1
4
Schoukens, Pintelon et al. (2012), whom optimized the signal design in such a manner that nonlinear
distortions can be detected. In an effort to separate the mechanical and GVS effects, stimuli were designed to
be mathematically uncorrelated. Figure 2 illustrates the frequency spectrums of both input signals (A) as well
as their representations in the time domain (B, C).
Mechanical
For each of the two directions, a different random phase realization was used to generate the perturbations.
The segment length of the signal was chosen to be 8.4 seconds, resulting in a frequency resolution of 0.119 Hz.
Nine frequencies were selected within a bandwidth of 0.119-4.167 Hz: respectively 0.119, 0.595, 0.833, 1.548,
2.024, 2.262, 2.738, 3.452 and 4.167 Hz. As the natural frequency of the head is estimated to be between 1.5
and 2.5 Hz in pitch and at approximately 2 Hz in yaw (Keshner, Cromwell et al. 1995; Keshner 2003), the
bandwidth of 0-4 Hz was considered to be appropriate to characterize the dynamics of the head-neck system in
roll. Furthermore, using a bandwidth of 4 Hz, vestibular reflexes due to the motion perturbation are known to
contribute equally or more than cervical reflexes (Keshner, Cromwell et al. 1995; Peng, Hain et al. 1996; Forbes,
de Bruijn et al. 2012). Both signals were designed to have a flat power in velocity.
Two different amplitude levels were implemented, A1 and A2. A1 perturbations had a root-mean-square (RMS)
velocity of 7.0 mm/s for the translational and 0.73 o/s for the rotational conditions, both of which were
doubled for the A2 perturbations. Compared to literature in which similar torso perturbations were applied
(Keshner, Cromwell et al. 1995; Forbes, de Bruijn et al. 2012) these values are seen to be relatively low. This
was done to match the relatively small movements evoked by GVS in the isolated head-neck system (Ehtemam,
Forbes et al. 2012). The selection of the minimal motion amplitudes was done during pilot testing.
GVS
The GVS stimulus was developed with a segment length of 5.6 seconds resulting in a frequency resolution of
0.1786 Hz. The bandwidth was chosen to be between 0.178 and 4.107 Hz, similar to stimuli developed by
Ehtemam, Forbes et al. (2012). To ensure sufficient signal-to-noise ratios (SNR) in the output responses only six
frequencies were selected: 0.178, 0.893, 1.250, 1.964, 3.036 and 4.107 Hz. A GVS amplitude of 4 mA was
chosen, ensuring sufficient comfort for the subject.
Figure 2: A) Frequency spectra of both signals (velocity spectrum is shown for the mechanical perturbation, showing flat
power). Scale of y-axis is not representative. B) T-A2 Position multisine with amplitude A2 C) GVS multisine
5
Data analysis
Time domain analysis
From the motion capture data, rigid bodies were constructed of the chair, torso and head respectively, using
the rigid body algorithms of the Qualisys software. Marker data was assessed per trial, and if regarded of
sufficient quality (i.e. no occlusions or poor position estimations) included in the definition of the
corresponding rigid body. A head coordinate system was defined at the estimated center of gravity of the head
oriented along the Frankfurt plane (see Figure 1B), (Yoganandan, Pintar et al. 2009). The torso and chair rigid
bodies were constructed from their markers with the local coordinate systems located at the T1 marker and
the chair back bottom marker. The first ten seconds of each trial were removed from the dataset in order to
accommodate the fade-in period of the platform. All position data was filtered with a second-order
Butterworth filter with a cut-off frequency of 30 Hz and velocity was calculated as its derivative.
System identification
To describe the kinematic responses to GVS and torso perturbations, frequency response functions (FRF) were
estimated. Data was first concatenated from the two repetitions. The smallest segment length which included
an integer number of both GVS and mechanical segments was 16.8 seconds. This resulted in a total of eight
combined segments in the 152 seconds trial data with each combined segment containing two mechanical
segments and three GVS segments.
Data was transformed into the frequency domain, and auto- and cross-spectral power spectra were calculated
and averaged over the eight 16.8 s segments. In Equation 1 and 2, U and Y respectively represent the Fourier
transforms of segment length Nd (number of samples) of the input perturbation and output motion
respectively. The * indicates the complex conjugate and D indicates the number of segments.
*
1
1 D
uu d d
dd
S U UD N
(1)
*
1
1 D
uy d d
dd
S U YD N
(2)
FRFs between the input perturbations and output motion were calculated. For the FRFs between input torso
motion and output head motion (kinematic FRFs, from now on described as kFRFs) and the FRFs with input GVS
and output head motion (galvanic FRFs, from now on described as gFRFs) an open-loop estimate (Equation 3)
was used. In this equation, y stands for the head kinematics output and u stands for the torso perturbation. FRF
gains were log transformed prior to calculating the subject average.
uy
uy
uu
SH
S (3)
While using these estimators, a linear relationship is assumed between the input and output signals. An
estimate on the linearity of the system is given by the coherence function; varying between 0 and 1, with 1
indicating a completely linear and noise free system. Coherence values less than one indicate the presence of
noise or nonlinearities present in the system. Coherences for head kinematics (γuy2) were calculated as in
Equation 4, and were considered significant if values were above the threshold level (Halliday, Rosenberg et al.
1995) as described by Equation 5.
6
2
2| |uy
uy
uu yy
S
S S
(4)
1
11 (0.05)Dp (5)
Statistical analysis
For a limited set of kFRFs and gFRFS, statistical analyses were performed at each frequency point using
repeated measures MANOVAs for both gain and phase simultaneously. For the kFRFs, the effects of amplitude
of the torso perturbation (A1, A2) and the presence of GVS were evaluated across the translational and
rotational conditions respectively, and for the gFRFs, the effects of mechanical perturbation amplitude (A1, A2)
and direction (T, R) were evaluated across all conditions with GVS. A significance of P = 0.05 was used for all
analyses.
7
3. Results
Mechanical perturbations
Kinematics
Figure 3 plots the subject averages of the global (YGH and ΦGH) and relative (YRH/ΦRH) head displacement for the
translation and rotation conditions during mechanical only and natural head sway conditions. Included are
torso input lateral translation (YT1) and roll rotation (ΦT1) which closely matched the inputs provided by the
platform (YChair and ΦChair, data not shown). For both directions, global head kinematics (YGH and ΦGH) followed
input torso perturbations YT1 and ΦT1 and increased with amplitude. In translation conditions YRH was similar in
shape and timing to ΦGH, indicating a coupled response typical of an inverted pendulum (1 DOF), and both
were more high frequent than YGH. On the other hand, in rotation conditions similarities in shape and timing
observed between ΦGH and YGH were not as obvious, which could indicate that the rotation conditions induce
less one-dimensional inverted pendulum-like responses than translation conditions. In addition, ΦGH showed
slightly larger amplitudes and more emphasis on higher frequencies than input ΦT1.
Figure 3: Time domain responses (positions) averaged over all subjects (n=7), shaded region ± standard error (SE) for the mechanical-only trials. Plotted are respectively torso input YT1/ΦT1, global head outputs YGH and ΦGH and relative head
outputs YRH/ΦRH.
Figure 4 presents (in blue) the RMS values for displacement of the head as a function of perturbation amplitude
A0 (natural head sway), A1 and A2, for the output measures YGH, ΦGH and YRH/ΦRH. Global RMS responses YGH
and ΦGH increased significantly with amplitude in translation (YGH, F2,5 = 408.641, P < 0.001; ΦGH, F2,5 = 6.734, P =
0.038) and rotation (YGH, F2,5 = 13.040, P = 0.01; ΦGH, F2,5 = 44.776, P = 0.001). Table A-4 in Appendix A
summarizes the significance of RMS value comparisons.
Input
Output
8
Figure 4: RMS displacement values of YGH, ΦGH and YRH/ΦRH for mechanical-only (blue) and combined (red) conditions at different amplitudes (A0, A1 and A2 respectively)
Autospectral densities of head kinematics in the perturbed direction (lateral translation and roll) for the
conditions without GVS are shown in Figure 5 for all subjects and the mean. The mechanically stimulated
frequencies (blue dots) show substantially higher power than the neighboring non-stimulated frequencies.
Spectral power at the harmonics of these frequencies was much smaller and therefore considered negligible.
An increase in amplitude led to an increase of power and more distinct peaks relative to non-stimulated points.
In translation conditions, power decreased at all points with increasing frequency reflecting inertial effects of
the head-neck system. This effect was not as readily observed in rotation conditions, as peaks leveled off at
higher frequencies.
Figure 5: Autospectral densities of head output translational (YGH) and rotational (ΦGH) averaged over 16.8 seconds for
the motion conditions without GVS. Grey: different subjects, black: mean across subjects. Blue dots: mechanically stimulated frequencies, red dots: (non-stimulated) GVS frequencies.
9
Dynamic response behavior
Figure 12, Figure 13 and Figure 14 present the kFRFs and coherences with input torso perturbation (YT1 or ΦT1)
and output global (YGH and ΦGH) and relative (YRH/ΦRH) kinematics for amplitudes A1 and A2. Mechanical only
conditions (A1-0 and A2-0) are presented in blue. Tables A-1 and A-2 in Appendix A summarize the significance
of gain and phase comparisons for the kFRFs in translational and rotational conditions respectively. Coherences
were high and above significance level for all global and relative kFRFs over the whole frequency range with the
exception of some points at low frequencies. Coherences increased with input amplitude; indicating that the
reduction in coherence at some frequencies was due to low SNR. Overall, the high coherences observed in all
these conditions justified the use of linear techniques for the kFRFs.
Our translation condition results were similar to those reported by Forbes, de Bruijn et al. (2012) where
anterior posterior perturbations were applied. For the YGH (Figure 12) a gain of approximately 1 and phase of 0o
indicated that the head-neck system compensated for the lateral torso motion up to approximately 1 Hz. The
natural frequency was around 1-2 Hz; thereafter gain decreased and phase lag increased. Up to 4 Hz the
response resembled a second-order response; however at the highest frequencies phase lag decreased. This
likely reflects higher order dynamics, as observed by Viviani and Berthoz (1975) and Forbes, de Bruijn et al.
(2012) between 4-8 Hz. Amplitude of the input had a significant effect on the YGH kFRFs around the natural
frequency (i.e. between 0.83 and 3.45 Hz, all values F2,5 > 5.939, P < 0.048) where an increased torso amplitude
led to decreased gain (A1 > A2).
Similarities between ΦGH and YRH were also observed in the kFRFs (Figure 13 and Figure 14). Gains increased
from 0 to approximately 2 Hz (i.e. the natural frequency) while phases stayed approximately level. Thereafter,
the gain leveled off and the phase eventually dropped to -180o for YRH and 0o for ΦGH (with an initial phase of
+180o). The lead behavior of the ΦGH kFRF is attributed to the sign of rotation used in the measurements. Input
amplitude had a significant effect on the kFRF of YRH between 0.83 and 4.17 Hz (all values except 3.45 Hz F2,5 >
7.484, P < 0.031) as an increase of motion amplitude led to a decreased gain (between 2.02 and 3.45 Hz) and
increased phase lag. Significant amplitude effects were found for the kFRF of ΦGH between 1.54 and 2.73 Hz (all
values F2,5 > 7.326, P < 0.033). Phase decreased with increased motion, though the effect on the gain
demonstrated no particular pattern.
In the rotation conditions, the ΦGH kFRF had a gain of 1.3 and phase close to 0o up to 1 Hz, which meant the
head rotated, and therefore tilted with the platform. Interestingly, the amplitude of the global head motion
was always larger than the platform motion. The gain further increased with frequency without any sign of
surpassing the natural frequency. This increase in gain was accompanied by a slow decrease of the phase
(ending around -50o at 4.17 Hz in the different conditions). Amplitude had a significant effect on the gain and
phase at only two frequency points (gain: A1 > A2 at 2.02 and 2.26 Hz; F2,5 > 13.612, P < 0.043 and phase: A1 <
A2 at 3.45 and 4.17 Hz; F2,5 > 7.987, P < 0.01).
For the ΦRH kFRF gain increased and phase decreased over the whole bandwidth (0.12-4.17 Hz). Amplitude had
a significant effect within the frequency range of 2.02-4.17 Hz (all values F2,5 > 7.719, P < 0.030) however these
changes did not reflect a consistent response in which gain increased and decreased with amplitude at various
frequency points. For the YGH kFRF, the natural frequency was observed to be at approximately 1-2 Hz. In
addition, the gain decreased significantly with amplitude from 1.54 Hz and up (all values F2,5 > 6.831, P < 0.037).
Galvanic vestibular stimulation
Kinematics
Figure 6 plots subject averages of the head kinematics in the time domain. One analyzed segment is shown
(16.8 s) containing three GVS segments of 5.6 s from the GVS only condition. The vestibular stimulus induced
lateral head translation and roll with obvious periodicity. The spectral power (Figure 7) was higher at the
stimulated frequencies relative to the non-stimulated frequencies during GVS only tests (M-00-1). At the lowest
10
(0.18 Hz) and highest (4.11 Hz) frequencies, power at the stimulated frequency was more comparable to the
neighboring frequencies, as similarly observed by Ehtemam, Forbes et al. (2012).
Figure 6: Time domain responses averaged over all subjects, ±SE, for GVS-only trial (M-00-1). Plotted are respectively the
GVS input signal, YHead and ΦGH.
Figure 7: Power spectra of M-00-1 for YHead and ΦGH. Indicated in red are the GVS frequencies. Indicated in blue are the (non-stimulated)
mechanical frequencies
Dynamic response behavior
Figure 15 and Figure 16 plot gFRFs and coherences for YGH and ΦGH in the GVS-only condition (black dotted line).
For both output measures across all frequencies, coherences were above significance level justifying linear
analysis techniques. Frequency influenced the level of coherence, which increased up to ~3.5 Hz and decreased
thereafter. The gains of both YGH and ΦGH were more or less level up to 2 Hz and decreased thereafter. This
behavior corresponded with the natural frequency of the head as also found in the mechanical conditions. For
ΦGH, phase dropped as well across the whole bandwidth, starting at 0o and ending below -200o. For the lowest
frequency stimulated (0.18 Hz) the phase of YGH was close to 180o, followed by a phase decrease ending around
-110o at 4.11 Hz.
Multiloop stimulation
Kinematics
In
Figure 8 subject averaged head kinematics are presented for amplitude A2, translation and rotation conditions
with and without GVS. For both mechanical directions, GVS in addition to the mechanical stimuli modified the
output responses. In translation conditions the RMS values (see Figure 4) of YGH and YRH increased significantly
with GVS (YGH, F1,6 = 8.683, P = 0.026; YRH, F1,6 = 9.645, P = 0.021). However, the increase in roll displacement
ΦGH due to the GVS was not significant. In the rotation conditions there was a significant increase of YGH (F1,6 =
11.084, P = 0.016) due to GVS while the increases in ΦGH and ΦRH RMS due to GVS were not significant.
11
Figure 8: Time domain responses (positions) averaged over all subjects, ±SE, for T-A2-0 and T-A2-1, R-A2-0 and R-A2-1
respectively. Plotted are respectively torso input YT1/ΦT1, YGH, ΦGH and YRH/ΦRH.
Figure 9 and Figure 10 plot the autospectral densities of the output head kinematics (YGH and ΦGH) for the
motion perturbation directions with GVS and mechanical inputs. Both the mechanically stimulated frequencies
(blue) and the GVS frequencies (red) are included. Translation perturbations induced higher power in
translation kinematics in comparison to rotation kinematics and vice-versa for rotation perturbations. For both
mechanical and galvanic stimulation points power was greater than at neighboring non-stimulated points.
However, if stimulated frequencies were close, one stimulus type (mechanical or galvanic) was dominant over
the other. Noise levels (i.e. power at non-stimulated points) increased during simultaneous stimulation as
compared to isolated mechanical or galvanic stimulation. In addition, during translation perturbations GVS
were always below mechanical peaks whereas during rotation perturbations GVS peaks were equivalent or
higher.
Figure 9: Autospectral densities for conditions with simultaneous stimulation, YGH
12
Figure 10: Autospectral densities for conditions with simultaneous stimulation, ΦGH
Dynamic response behavior
For the most part, the addition of GVS decreased coherence (see Figure 12, 13 and 14) for global and relative
kFRFs. The drop in coherence was less severe with increased motion amplitude for all kFRFs, indicating the
dominance of mechanical perturbations at higher amplitudes. For translation conditions, this was most evident
for YRH and ΦGH kFRFs at frequencies below 2 Hz, while for the rotation condition it was evident in all three
output measures. On the other hand, the addition of mechanical perturbations both increased and decreased
coherence in the gFRFs. The changes indicate some form of interference between the two stimuli at those
frequencies.
kFRFs were substantially influenced by the addition of GVS. Most notably, in the YGH kFRF gain increased at high
frequencies (> 2.26 Hz, all values F2,5 > 11.007, P < 0.015). The ΦGH and YRH kFRF gains decreased at low
frequencies (between 0.59 and 1.54 Hz, all values F2,5 > 7.877, P < 0.028). This indicates an increase in high
frequency global head motion and a decrease in low frequency relative head motion. Additionally, in the YRH
kFRF, from 2.73 till 4.17 Hz gain increased with GVS (all values F2,5 > 8.364, P < 0.025). During rotation
conditions some statistically significant differences were observed at various frequency points in all kFRFs when
GVS was present. However their effects were irregular across the bandwidth with amplitudes both increasing
and decreasing gain and phase. The exception to this was the significant gain decrease in the YGH kFRF between
1.54 and 2.26 Hz (all values, F2,5 > 6.908, P < 0.036).
Substantial modulations of gFRFs were observed when mechanical perturbations were applied and across the
amplitude of the perturbation. Table A-3 in Appendix A summarizes the significance of gain and phase
comparisons for the gFRFs. Gains increased at lower frequencies with increasing motion amplitude (i.e. from
A0-to-A2), indicating a non-linear relationship with the input mechanical perturbations. YGH gFRF gains
increased significantly with amplitude between 0.17 and 1.96 Hz (0.17 Hz: F4,24 = 5.314, P = 0.004; 1.25 Hz: F4,24
= 2.949, P = 0.041, other values F2,5 > 10.176, P < 0.043) while ΦGH gFRF gains increased significantly with
amplitude between 0.17 and 1.25 Hz (0.17 Hz: F4,24 = 3.059, P = 0.036; 0.89 Hz: F2,5 = 27.294, P = 0.011 1.25 Hz:
F4,24 = 3.243, P = 0.029). No significant phase changes were found between conditions for the YGH and ΦGH
kFRFs.
Interestingly, the increase in gain with amplitude was larger in the translation conditions for both YGH
(significant between 0.17-1.96 Hz, all values F2,5 > 6.387, P < 0.042) and ΦGH (significant between 0.89-1.96 Hz,
all values F2,5 > 9.951, P < 0.018). These gain changes are plotted in Figure 11 as a function of the head
13
acceleration RMS (YGH and ΦGH) for each frequency point (f1-f6) and mechanical perturbation amplitude (A0, A1
and A2). As GVS is known to modulate the firing rate of the vestibular afferent output (Fitzpatrick and Day
2004), the objective was to associate the gain changes to either the perturbation condition (translational or
rotational) or the underlying kinematics which define the mean firing rate. Similarity of slopes between
translation and rotations conditions would reflect a sensory only modulation which is related to the mean firing
rate of the afferents. While at the lower frequencies (e.g. f1-f3) gain increases were observed close to linear
with the underlying mean kinematic responses, at the higher frequencies (e.g. f4-f6), primarily gains remained
unchanged between conditions which is represented by horizontal lines. Plotting gains against head rotational
acceleration RMS revealed similarities in slope across perturbation conditions, which indicate a sensory only
relationship. For example, the condition with the largest rotational acceleration (T-A2-1, 192 o/s) also showed
the largest gain increase. However, when plotting gains against head translational acceleration RMS, slopes
changed between translation conditions and rotation conditions, with the rotation showing a higher slope. This
suggests that gain changes could also be dependent on perturbation condition (e.g. underlying head-neck
mechanics).
Figure 11: Gain per frequency over the different translational and rotational conditions for GVS-to-YGH (upper row) and GVS-to-ΦGH (bottom row), plotted against RMS head acceleration YGH,acc (left column) and ΦGH,acc (right column). Points
plotted in blue, green and red are respectively GVS with A0 (only GVS), with A1 and with A2. The different lines represent the different frequency points.
14
Figure 12: kFRFs YT1-to-YGH (translation conditions) and ΦT1-to-YGH (rotation conditions). Blue: conditions without GVS, red: conditions with GVS
15
Figure 13: kFRFs YT1-to-ΦGH (translation conditions) and ΦT1-to-ΦGH (rotation conditions). Blue: conditions without GVS, red: conditions with GVS
16
Figure 14: kFRFs YT1-to-YRH (translation conditions) and ΦT1-to-ΦRH (rotation conditions). Blue: conditions without GVS, red: conditions with GVS
17
Figure 15: gFRFs GVS-to-YGH. Dotted line indicates GVS condition without motion perturbation (M-00-1)
18
Figure 16: gFRFs GVS-to-ΦGH. Dotted line indicates GVS condition without motion perturbation (M-00-1)
19
4. Discussion
The goal of this study was to assess the validity of the superposition principle during combined lateral torso
perturbations and continuous galvanic vestibular stimulation without visual feedback (eyes-closed conditions).
It was shown that the combined perturbation elicits non-linear integration of vestibular sensory information as
between simultaneous perturbation and isolated perturbation responses significant differences were observed
for gain and phase in the FRFs. Experimentally it was proven that direction of torso motion and amplitude of
the perturbations affect the ability to identify system dynamics, however for all torso perturbations tested
coherent kinematic and GVS transfer functions were found.
Vestibular and mechanical perturbations show coherent motion at all amplitudes
Simultaneous perturbation experiments were successfully carried out, as significantly coherent head motions in
roll and lateral translation were observed in both kinematic and galvanic FRFs for all amplitudes and directions
across the frequency bandwidth. Coherence increased with amplitude during mechanical perturbations,
indicating an increased SNR. Although motion related to the mechanical perturbations were larger than
equivalent measures during vestibular stimulation, significant coherence (> 0.5) was found for the gFRFs. This
indicates the opportunity to increase mechanical input if necessary or applicable for future studies.
The high coherences together with the mathematically uncorrelated design of the inputs should facilitate
analysis of separate responses to evaluate the superposition principle. However, contrary to the work of
Cencairini and Peterka (2006), the addition of GVS to the mechanical perturbation indicated interference
between the two inputs by decreasing coherence. The effect on the coherence decreased with amplitude of
the mechanical perturbation, indicating a dominance of the mechanical inputs at the higher amplitude. This
was possibly attributed to either increased noise levels or distortion effects (e.g. dominance of one output over
the other) when frequency points of the different stimuli were close to one another. The incongruence with
results observed by Cencairini and Peterka (2006) is likely due to amplitude differences where we used a
galvanic stimulus approximately five times larger. Regardless, coherence was high in all conditions justifying
linear system identification techniques. Nevertheless, while linearity could be assumed within conditions,
nonlinear behavior which violated the superposition principle was observed between responses to
simultaneous perturbations and responses to isolated perturbations, as gains and phases changed with the
addition of GVS in the kFRFs and motion in the gFRFs.
Similarities between responses to anterior-posterior and lateral perturbations suggest the head-neck system
behaves similar in both directions. During translation conditions the system behaved as a damped, close to
linear second-order system very similar to dynamics shown by Keshner (2003) and Forbes, de Bruijn et al.
(2012) for anterior-posterior translations. However, the kFRFs in the rotation conditions resembled the
responses of elderly subjects from the studies of Keshner and Chen (1996) and Keshner (2000) rather than
responses of younger subjects (Keshner, Cromwell et al. 1995; Keshner 2000) to pitch rotations during a natural
stabilization task (mental arithmetic). Gains gradually increased and phase gradually decreased over the whole
bandwidth, reflecting a second-order underdamped system with resonance occurring at the higher frequencies
(> 2 Hz). In general, compared to the younger subjects, the elderly subjects as well as our subjects showed a
reduced ability to stabilize the head in space in response to vertical torso perturbations. For the elderly
subjects this response was attributed to ineffective reflex mechanisms, which suggests that for the rotation
conditions (amplitudes) tested in our study, there might be a large reliance on passive system mechanics and
little involvement of reflexive mechanisms.
Non-linear integration of vestibular sensory information
Within translation conditions, Keshner (2003) postulated that the system relies heavily on the passive
mechanics, with a possible role for vestibular reflexive control at lower frequencies (< 1 Hz) as the head moved
20
together with the torso (phase equals 0o, gain equals 1). However, modulation of the YGH kFRF (increased gain)
in translation conditions at high frequencies (> 2 Hz) during simultaneous perturbations suggests mechanical
influence of the vestibular system at frequencies higher than previously reported (Keshner 2003). The
increased gain with the presence of GVS might also indicate that the vestibular system becomes less effective
in damping the mechanically perturbed frequencies (Keshner 2003). This could perhaps be attributed to
sensory reweighting by the central nervous system. The increase variability or noise in a sensory signal, which
may be caused by GVS, is predicted to lower the importance of the sensory channel (van der Kooij, Jacobs et al.
1999; Cencairini and Peterka 2006), and subsequently affect stabilization.
Assuming a reduced importance of vestibular input, one could assume a proportional increase in
proprioceptive information. Examining the of YRH and ΦGH kFRFs, which reflect muscle spindle activity and a
combination of muscle spindles and semicircular canal activity, gains decreased thereby improving stabilization
at the lowest frequencies with the addition of GVS. Neck proprioceptive inputs are known to have an influence
on the vestibular response, as various neurons in the vestibular nucleus also receive input from the muscle
spindles (Kasper, Schor et al. 1988). The overall interaction between neck proprioceptive inputs and canal
neurons changes across frequencies, showing the influence of both inputs at lower frequencies and a possible
dominance of the vestibular input at higher frequencies (Wilson, Yamagata et al. 1990), which might explain
the different modulation at low and high frequencies.
Alternatively, one could argue that the vestibular contribution during mechanical only conditions may not be as
high in our results due to the small amplitudes as vestibular afferents are known to possess nonlinear threshold
properties. In the study by Gurses, Dhaher et al. (2005) which implemented small anterior-posterior
translations, results showing modulations with perturbation amplitude were explained by means of an
simplistic inverted pendulum model with position and velocity sensory thresholds. In line with this, in our study
mean head velocities for all conditions were seen to be below with vestibular threshold estimates (Kingma
2005) for the perception of linear velocity, around 104 mm/s at 0.1 Hz (T-A2 20 mm/s, R-A2 8 mm/s
respectively) but thresholds are reported to be lower at higher frequencies (e.g. 61 mm/s at 0.25 Hz, (Zupan
and Merfeld 2008)). Assuming Keshner’s theory on damping via vestibular contributions, an increase in motion
amplitude may therefore lead to therefore increased damping.
Within the gFRFs, an enhanced sensitivity to GVS was found at the low frequencies (below ~1-2 Hz) for the
conditions with combined perturbations. For both translational and rotational mechanical input, gFRF gain
increased significantly with motion perturbation amplitude. However, the magnitude of the changes differed
across perturbation directions and depended on the measured mean kinematics. From previous studies
(Popov, Smetanin et al. 1986; Smetanin, Popov et al. 1988) it is known that several factors can influence the
magnitude and direction of the body sway, such as orientation and the presence of additional proprioceptive
cues. Most importantly for our study, it has been suggested by Inglis, Shupert et al. (1995) and Hlavacka,
Shupert et al. (1999) that galvanic stimulation is more effective in producing body sway when the body is
already in motion, with the magnitude of the effect of vestibular stimulation increasing with platform velocity.
From animal studies (Goldberg, Fernandez et al. 1982; Goldberg, Smith et al. 1984) it is known that galvanic
currents modulate the ongoing discharge of individual irregularly firing canal afferents in the same way as
angular accelerations. Within the semicircular canals at single sensory unit level responses to GVS stimulation
are shown to sum up with the response to natural acceleration, increasing the firing rate of the afferents
(Lowenstein 1955). A larger natural acceleration leads to an increased mean firing rate and therefore causes a
larger GVS sway response. It is likely that this effect is less present at higher frequencies (i.e. above the
estimated natural frequency of the system) due to inertial properties of the system.
Although sensory modulation was attributed to the underlying kinematics, Figure 11 also indicated changes to
be associated with the motion perturbation condition. In rotation conditions the gain increased more rapidly
(i.e. higher slope) than translation conditions when plotted against the RMS head translational acceleration.
This suggests the possible influence of the head-neck mechanics induced by each perturbation direction.
21
However, no reasonable explanation could be obtained from the current data to account for such an effect.
Therefore, further studies investigating these two effects (mechanical versus sensory) would help to further
understand the vestibular influence on head-neck stabilization during different conditions.
5. Conclusions
Continuous GVS and low-level torso perturbations can be used successfully together with system
identification techniques to identify the system dynamics as coherences above significance level were
found for all conditions;
System responses close to linear were found for the isolated mechanical and galvanic perturbations,
therefore facilitating the analysis of separate responses to evaluate the superposition principle;
The superposition principle does not hold during simultaneous perturbations as the addition of GVS
and motion to the isolated mechanical and galvanic perturbations changed the vestibular contribution
suggesting non-linear integration of vestibular information;
Neither amplitude nor direction of the mechanical perturbations was seen to be a determining factor
in the ability to provide coherent GVS transfer functions;
Across the tested mechanical perturbations, results of translation conditions compared to rotation
conditions were more reliable with change of perturbation amplitude and addition of GVS as more
consistent patterns were found within and across conditions.
22
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A-1
Appendix A. Statistical Tables
Table A-1: Effects of amplitude and presence of GVS in translation conditions on group mean kFRF gain and phase values at different frequency points (0.119-4.167 Hz)
FRF Gain Frequency GVS Amplitude
(Hz) F2,5 P F2,5 P
YT1 YGH 0.119 0.386 0.698 0.880 0.471
0.595 13.058 0.010 2.506 0.176
0.833 6.367 0.042 8.103 0.027
1.548 11.316 0.014 9.179 0.021
2.023 4.689 0.071 10.329 0.017
2.262 12.039 0.012 7.439 0.032
2.738 12.235 0.012 5.939 0.048
3.452 11.007 0.015 6.062 0.046
4.167 41.715 0.001 5.216 0.060
YT1 ΦGH 0.119 5.149 0.061 0.658 0.558
0.595 8.738 0.023 0.838 0.485
0.833 9.873 0.018 16.750 0.006
1.548 8.427 0.025 23.486 0.003
2.023 4.698 0.071 27.555 0.002
2.262 13.467 0.010 19.602 0.004
2.738 10.117 0.017 7.326 0.033
3.452 2.615 0.167 2.779 0.154
4.167 3.532 0.111 2.488 0.178
YT1 YRH 0.119 0.312 0.745 3.575 0.109
0.595 7.877 0.028 0.971 0.440
0.833 8.835 0.023 11.093 0.015
1.548 11.523 0.013 12.465 0.011
2.023 5.239 0.059 14.556 0.008
2.262 12.205 0.012 11.206 0.014
2.738 10.190 0.017 10.470 0.016
3.452 8.364 0.025 5.393 0.056
4.167 10.199 0.017 7.484 0.031
Table A-2: Effects of amplitude and presence of GVS in rotation conditions on group mean kFRF gain and phase values at different frequency points (0.119-4.167 Hz)
FRF Gain Frequency GVS Amplitude
F2,5 P F2,5 P
ΦT1 YGH 0.119 24.605 0.003 0.239 0.796
0.595 0.125 0.885 5.412 0.056
0.833 3.611 0.107 4.174 0.086
1.548 3.299 0.122 25.926 0.002
A-2
Table A-2 (resumed)
2.023 2.960 0.142 45.505 0.001
2.262 2.905 0.146 6.908 0.036
2.738 2.530 0.147 24.362 0.003
3.452 5.180 0.060 28.556 0.002
4.167 3.014 0.138 6.831 0.037
ΦT1 ΦGH 0.119 12.113 0.012 0.420 0.678
0.595 0.110 0.898 1.149 0.389
0.833 1.413 0.326 0.094 0.911
1.548 3.862 0.097 3.280 0.123
2.023 11.912 0.013 160.275 < 0.001
2.262 14.705 0.008 13.612 0.009
2.738 4.444 0.078 2.982 0.140
3.452 4.671 0.072 7.987 0.028
4.167 1.708 0.272 60.919 < 0.001
ΦT1 ΦRH 0.119 57.690 < 0.001 0.250 0.788
0.595 0.098 0.908 1.613 0.288
0.833 1.754 0.265 0.020 0.980
1.548 3.338 0.120 2.681 0.162
2.023 17.862 0.005 69.995 < 0.001
2.262 14.322 0.009 10.307 0.017
2.738 5.237 0.059 2.382 0.188
3.452 4.341 0.081 7.719 0.030
4.167 1.303 0.350 59.296 < 0.001
Table A-3: Effects of torso motion direction and amplitude in translation and rotation conditions on group mean gFRF gain and phase values at different frequency points (0.179-4.107 Hz)
FRF Gain Frequency Direction Amplitude
(Hz) F2,5 P F2,5 P
GVS YGH 0.1791 6.387 0.042 2.073 0.288
0.893 17.255 0.006 17.563 0.020
1.2502 12.701 0.011 2.031 0.293
1.964 11.036 0.015 10.176 0.043
3.036 0.225 0.806 4.067 0.139
4.107 3.347 0.120 0.926 0.547
GVS ΦGH 0.1793 1.595 0.291 2.806 0.211
0.893 23.262 0.003 27.294 0.011
1.2504 9.951 0.018 5.301 0.101
1.964 10.231 0.017 6.895 0.072
3.0365 0.277 0.769 8.022 0.059
4.1076 2.184 0.208 3.140 0.187
Mauchly's Test of Sphericity violated for numbered entries, values with adjusted degrees of freedom: 1 F4,24 = 5.314, P = 0.003; 2 F4,24 = 2.949, P = 0.041; 3 F4,24 = 3.059, P = 0.036; 4 F4,24 = 3.242, P = 0.029; 5 F4,24 = 1.715, P = 0.179; 6 F4,24 = 0.700, P = 0.599;
A-3
Table A-4: Effects of presence of GVS and amplitude on group mean RMS displacement values
Direction Measure GVS Amplitude
F1,6 P F2,5 P
Translation YGH 8.683 0.026 408.461 < 0.001
ΦGH 3.801 0.099 6.734 0.038
YRH 9.645 0.021 5.532 0.054
Rotation YGH 11.084 0.016 13.040 0.010
ΦGH 4.422 0.080 44.776 0.001
ΦRH 5.124 0.064 3.474 0.113
Table A-5: Effects of torso motion direction and amplitude on group mean eFRF gain and phase values
FRF Gain Frequency Direction Amplitude
(Hz) F2,5 P F2,5 P
YGH EMG 0.119 33.112 0.001 0.733 0.526
0.595 5.853 0.049 10.468 0.016
0.833 8.317 0.026 3.559 0.109
1.548 8.091 0.027 2.397 0.186
2.023 5.164 0.061 0.906 0.462
2.262 1.237 0.336 4.239 0.084
2.738 10.389 0.017 0.547 0.610
3.452 13.760 0.009 1.477 0.313
4.167 8.251 0.026 2.069 0.221
ΦGH EMG 0.119 3.931 0.094 3.911 0.095
0.595 9.408 0.020 3.856 0.097
0.833 26.653 0.002 5.777 0.050
1.548 68.063 0.000 0.895 0.465
2.023 5.971 0.047 2.765 0.155
2.262 12.059 0.012 2.681 0.162
2.738 1.752 0.265 0.117 0.892
3.452 2.992 0.140 0.158 0.858
4.167 1.803 0.257 0.119 0.573
YRH EMG 0.119 0.009 0.992
0.595 3.477 0.113
0.833 1.864 0.248
1.548 0.778 0.508
2.023 0.196 0.828
2.262 0.361 0.714
2.738 0.153 0.862
3.452 0.431 0.672
4.167 0.245 0.779
ΦRH EMG 0.119 0.057 0.945
0.595 3.576 0.113
0.833 3.802 0.099
1.548 0.886 0.468
2.023 1.147 0.389
2.262 2.223 0.204
2.738 0.583 0.592
3.452 0.783 0.506
4.167 9.276 0.021
A-4
Appendix B. EMG measurements and analysis
Apparatus For all nine subjects, EMG of eight superficial neck muscles was recorded using bipolar microelectrodes and
TMSi Porti system (TMSi, Enschede, The Netherlands). Bilateral sternocleidomastoid (SCM), splenius (SPL),
levator scapulae (LS) and trapezius (TRAP) were measured at 2 kHz.
Procedures Maximum force trials were performed in lateral direction with the subjects pushing their heads against the
hand of one of the experimenters. This was done to check EMG measurement quality as well as for
normalization purposes. These five seconds long trials were performed at both sides of the head (left, right)
two times before and two times after the experiment.
Data analysis EMG data was processed for the five conditions without GVS, as surface EMG during conditions with GVS
possessed substantial stimulation artifact. EMG data was aligned in time with the motion capture data,
bandpass filtered at 20 and 400 Hz, rectified and normalized to the maximum push tests. All eight muscles
were also used to calculate a weighted EMG signal (see Equation A-1) following methods similar to those of
(Kiemel, Elahi et al. 2008). Per subject the weights wj were optimized simultaneously over all conditions, to
maximize the coherence γre2 at the perturbed frequencies between head kinematics and the weighted EMG
signal. This was done implementing the constraint that the sum of the absolute values of all wj equaled one.
Weights of the right and left muscles were used as positive and negative values respectively generating a signal
which varied around zero.
, , , , , , , ,
, , , , , , , ,
( ) ( ) ( ) ( ) ( )
( ) ( ) ( ) ( )
w scm r scm r spl r spl r ls r ls r trap r trap r
scm l scm l spl l spl l ls l ls l trap l trap l
e t w e t w e t w e t w e t
w e t w e t w e t w e t
(A-1)
System identification
To describe the EMG response to the torso perturbation, frequency response functions (FRF) were estimated.
Data was concatenated from the two repetitions performed, and to improve the estimation for EMG data
where only mechanical perturbations were applied, 18 segments of 8.4 s were used. For the EMG FRFs (from
now on described as eFRFs) which described the FRF from input head motion to output (weighted) neck EMG, a
closed loop estimator was used, Equation A-2. In this equation, u stands for the head kinematics input, e stands
for the weighted neck EMG and r stands for the torso perturbation. Coherence for EMG (γre2) was calculated as
in Equation A-3.
reue
ru
SH
S (A-2)
22 | |re
re
rr ee
S
S S
(A-3)
Results As an example, Figure A-1 shows the autospectral densities for the right and left LS muscles respectively.
Similar autospectral densities were calculated for the other muscles. It is visible that with increase of
amplitude, the mechanically stimulated frequencies increase in power compared to neighboring frequencies.
Accordingly, the natural sway condition (M-00-0) shows no increase in power at these frequencies.
Additionally, direction of motion is shown to have an influence on the activity in the muscle.
A-5
Dynamic response behavior
Figure A-2 shows the eFRFs of head kinematics-to-weighted EMG for global velocities ẎGH, ̇GH and local
velocities ẎRH/ ̇RH for both translation (left columns) and rotation (right columns) conditions. Regardless of
amplitude, in translation conditions coherence was smallest at the lowest frequencies (< 1 Hz), while in
rotation conditions coherence was smallest between 0.5-1.5 Hz. Coherence increased with amplitude and
therefore showed values above significance level above 2 Hz (translation condition) and above 2.7 Hz (rotation
conditions) for amplitude A1 and above 0.8 Hz (translational condition) and above 2 Hz (rotation condition) for
amplitude A2 respectively. Over all conditions and measures, amplitude did not cause significantly changes.
However, significant changes occurred between directions at the lower frequencies and highest frequencies for
YGH (< 1.55 Hz and > 2.74 Hz, all values P < 0.049 and F2,5 > 5.853) and at the lower and mid-frequencies for ̇GH
(< 2.62 Hz, all values P < 0.047, P > 5.971). Table A-5 in Appendix A summarizes the significance of gain and
phase comparisons for the eFRFs.
In general, in the translation conditions the ẎGH and ̇GH eFRFs resembled those from Forbes, de Bruijn et al.
(2012). For both amplitudes, the ẎGH eFRF indicated a sensitivity to velocity until approximately 1 Hz (slope of 0,
phase between -90-0o) with a shift to a sensitivity to acceleration at higher frequencies (slope of +1, phase
between 50-90o). The gains of the ̇GH and ẎRH eFRF showed a sensitivity to position (slope of -1) up to
approximately 1 Hz followed by sensitivity to velocity and acceleration thereafter (gain slope of 0, +1). Phases
of ̇GH were reversed 180o with respect to this gain observation, in accordance with the previous observed sign
for the rotation.
For the rotation conditions, especially the ẎGH showed similarities to EMG measurements done by Keshner,
Cromwell et al. (1995) and Keshner (2000) during pitch rotations. In those studies a U-shaped pattern of
response was described when plotted against trunk velocity, with gains decreasing at lower frequencies (below
2.15 Hz) and increasing sharply thereafter, accompanied by a 180o phase shift. Our ẎGH eFRFs, suggested
sensitivity to position until 1-2 Hz (decrease, slope of -1) followed by acceleration sensitivity (slope of +1)
indicated by a sharp gain increase (comparable in magnitude to the decrease). Contrary to R-A2-0 which
according to the gain shows a shift in phase from position (-90o) to acceleration (90o) between 1-2 Hz, the
phase of R-A1-0 increases gradually over the whole frequency range from -90o to 90o. Similar to ̇GH and ẎRH in
Figure A-1: Example autospectral densities of right and left LS muscles respectively. Plotted from left to right are the translation, rotation and no motion conditions. Grey lines indicate the different subjects while black line represents mean.
Blue dots indicate mechanically stimulated frequencies.
A-6
translation conditions, the ̇GH and ̇RH eFRFs showed sensitivity to position (slope of -1) up to approximately 1
Hz followed by sensitivity to acceleration thereafter (gain slope of 0, +1).
The ẎGH eFRF has been previously associated with otolith characteristics (Forbes, de Bruijn et al. 2012) which
have been described in animal studies to have sensitivity towards velocity and acceleration. The gain and phase
behavior in the translational conditions were in agreement with these observations. However, the ẎGH eFRF of
the rotational conditions also displayed position sensitivity at the lowest frequencies. This might indicate the
involvement of other sensory functions (e.g. muscle spindle activity) due to the change of perturbation type.
For both translation and rotation conditions, sensitivities in position and velocity for ̇GH and ẎRH/ ̇RH were
associated with the velocity sensitivity of the semicircular canals, and the position and velocity sensitivities of
muscle spindles.
A-7
Figure A-2: eFRF ẎGH, ̇GH and ẎRH/ ̇RH - Weighted EMG. Results are averaged over all subjects. Gains having a slope of -1, 0 and 1 and phases of -90, 0 and 90o indicate sensitivity of EMG to position, velocity and acceleration respectively.
