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The walking speed-dependency of gait variability in bilateral vestibulopathy and its association with clinical tests of vestibular function

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Understanding balance and gait deficits in vestibulopathy may help improve clinical care and our knowledge of the vestibular contributions to balance. Here, we examined walking speed effects on gait variability in healthy adults and in adults with bilateral vestibulopathy (BVP). Forty-four people with BVP, 12 healthy young adults and 12 healthy older adults walked at 0.4 m/s to 1.6 m/s in 0.2 m/s increments on a dual belt, instrumented treadmill. Using motion capture and kinematic data, the means and coefficients of variation for step length, time, width and double support time were calculated. The BVP group also completed a video head impulse test and examinations of ocular and cervical vestibular evoked myogenic potentials and dynamic visual acuity. Walking speed significantly affected all gait parameters. Step length variability at slower speeds and step width variability at faster speeds were the most distinguishing parameters between the healthy participants and people with BVP, and among people with BVP with different locomotor capacities. Step width variability, specifically, indicated an apparent persistent importance of vestibular function at increasing speeds. Gait variability was not associated with the clinical vestibular tests. Our results indicate that gait variability at multiple walking speeds has potential as an assessment tool for vestibular interventions.
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The walking speed-dependency
of gait variability in bilateral
vestibulopathy and its association
with clinical tests of vestibular
function
Christopher McCrum
1,2*, Florence Lucieer3, Raymond van de Berg3,4, Paul Willems1,
Angélica Pérez Fornos
5, Nils Guinand5, Kiros Karamanidis6, Herman Kingma
3,4 &
Kenneth Meijer
1
Understanding balance and gait decits in vestibulopathy may help improve clinical care and our
knowledge of the vestibular contributions to balance. Here, we examined walking speed eects on
gait variability in healthy adults and in adults with bilateral vestibulopathy (BVP). Forty-four people
with BVP, 12 healthy young adults and 12 healthy older adults walked at 0.4 m/s to 1.6 m/s in 0.2 m/s
increments on a dual belt, instrumented treadmill. Using motion capture and kinematic data, the means
and coecients of variation for step length, time, width and double support time were calculated. The
BVP group also completed a video head impulse test and examinations of ocular and cervical vestibular
evoked myogenic potentials and dynamic visual acuity. Walking speed signicantly aected all gait
parameters. Step length variability at slower speeds and step width variability at faster speeds were
the most distinguishing parameters between the healthy participants and people with BVP, and among
people with BVP with dierent locomotor capacities. Step width variability, specically, indicated an
apparent persistent importance of vestibular function at increasing speeds. Gait variability was not
associated with the clinical vestibular tests. Our results indicate that gait variability at multiple walking
speeds has potential as an assessment tool for vestibular interventions.
Since the chance observation of a dog with acute unilateral vestibulopathy who demonstrated less imbalance
during running than during walking1, the interactions of gait velocity, imbalance and vestibular symptoms in
people with vestibulopathy have become a topic of great interest. Inspired by the observation in the dog, Brandt,
et al.1 demonstrated with a simple setup that humans with acute unilateral vestibulopathy could run with less
deviation to the aected side than while walking. Since then, reductions in temporal gait variability and reduc-
tions in stride length variability in bilateral vestibulopathy (BVP) during faster, compared to slower walking have
been observed24. BVP, a severe bilateral reduction of vestibular function that results in severe balance decits
and an increased fall risk510, was recently dened by the Bárány Society11. Interestingly, the same studies revealed
that patients with BVP do not self-select walking speeds that minimize temporal or spatial gait variability24,
suggesting that these are not the only source of instability or ineciency with which people with BVP must cope.
However, further research into the relationships between vestibulopathy, walking speed and gait variability is
needed to conrm and expand on these previous ndings, as these three previous studies had some potential
1Department of Nutrition and Movement Sciences, NUTRIM School of Nutrition and Translational Research in
Metabolism, Maastricht University Medical Centre+, Maastricht, The Netherlands. 2Institute of Movement and Sport
Gerontology, German Sport University Cologne, Cologne, Germany. 3Division of Balance Disorders, Department of
Otolaryngology, Head and Neck Surgery, Maastricht University Medical Centre+, Maastricht, The Netherlands.
4Faculty of Physics, Tomsk State University, Tomsk, Russian Federation. 5Service of Otorhinolaryngology and Head
and Neck Surgery, Department of Clinical Neurosciences, Geneva University Hospitals, Geneva, Switzerland. 6Sport
and Exercise Science Research Centre, School of Applied Sciences, London South Bank University, London, UK.
*email: chris.mccrum@maastrichtuniversity.nl
OPEN
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drawbacks, namely a limited number of gait parameters being analysed2, too few strides1215 for a robust analysis
of gait variability2,3, the use of only preferred walking speeds or percentages of preferred walking speeds (ecolog-
ically valid, but less control over inuencing factors)24, small sample size4, lack of a healthy control group3,4 and
the presence of sham vestibular stimulation in the control condition4. e study of balance and gait decits in
BVP is both important for improving clinical care and for objective quantication of the eects of novel inter-
ventions, such as vestibular implants16,17. Furthermore, it is fundamental to our understanding of the vestibular
contributions to gait and balance control.
e sensory contributions to gait appear to depend on walking speed, which may partly explain the above
described ndings and will aect walking speed selection in people with vestibulopathy. Visual perturbations
such as distorting prisms or closed eyes have reducing impact on most gait variability parameters as one walks
faster18,19 with the exception of step width variability, which appears to increase with visual perturbation at faster
walking speeds19. Similarly, vestibular perturbations via galvanic vestibular stimulation have less impact on gait
direction and variability at higher speeds20,21. Additionally, the vestibular inuence on lower limb muscles (deter-
mined by examining vestibulo-muscular coupling via lower limb muscle electromyography during vestibular
stimulation) is selectively suppressed with increased cadence and speed during walking22,23, purported to be
related to a shi in the control mechanisms of mediolateral stability with increasing walking speeds from active
stabilization at the lower limb joints during the stance phase to foot placement22,24. Despite selective suppression
of the vestibular inuence on some lower limb muscles at faster walking speeds, signicant increases in frontal
spatial variability with increasing walking speeds have been reported in BVP4, suggesting that vestibular informa-
tion remains important for mediolateral stability during gait at faster speeds.
To further investigate the walking speed dependency of gait variability in vestibulopathy, we analyzed the gait
of people with BVP and of healthy control participants. We aimed to determine the eects of systematic increases
in walking speed on spatiotemporal gait parameters and their variability in these participant groups. Secondly,
we aimed to assess if these parameters would dierentiate between healthy participants, and participants with
BVP who could and could not complete all of the planned walking speed trials. We hypothesized that, for all par-
ticipants, step and double support time and step length variability would systematically reduce with increases in
walking speed, whereas step width variability would systematically increase, in agreement with previous work24.
We further postulated that, based on earlier studies and despite their limitations described above2,3, step and dou-
ble support time and step length variability at slower walking speeds would be most distinguishing between the
healthy control participants and patients with BVP, and also between the patients with BVP that could completely
and only partly complete the measurement protocol, whereas step width variability would be most distinguishing
at faster walking speeds, based on one study showing an increase in BVP4. Additionally, we conducted an explor-
ative analysis in the patient groups examining correlations between the outcomes of the most distinguishing gait
parameters identied and clinical vestibular tests conducted as part of a larger clinical study (video head impulse
test [vHIT], ocular and cervical vestibular evoked myogenic potentials [oVEMP and cVEMP] and dynamic visual
acuity [DVA]) that are indicative of vestibular functional integrity and commonly used in clinical settings, with
the aim to explore if these tests could give an indication about gait-related function in BVP.
Methods
Participants. Forty-four people with BVP participated in this study (22 males, 22 females; age: 57.6 ± 11.5
years, age range: 21 to 74; height: 174.5 ± 9.7 cm; weight: 80.4 ± 17 kg). Inclusion criteria were a prior diagnosis
of bilateral vestibular hypofunction at the Maastricht University Medical Centre+ (imbalance and/or oscillopsia
during locomotion and summated slow phase mean peak velocity of the nystagmus of less than 20°/s during
bithermal caloric tests) and the self-reported ability to walk independently without assistance. Please note that
this study began prior to the publication of the Bárány Society guidelines11, which are slightly dierent. Potential
participants were not included if they were unable or unwilling to stop taking anxiety or depression medication
for the week before the measurements. In addition, two healthy control groups comprised of 12 healthy younger
adults (Young; 5 males, 7 females; 25.1 ± 2.8 years; 174.9 ± 7.3 cm; 72.6 ± 13.5 kg) and 12 healthy older adults
(Older; 8 males, 4 females; 71.5 ± 4.8 years; 171.5 ± 9.1 cm; 79.5 ± 11.8 kg) with no history of balance or gait dif-
culties and no history of dizziness participated in this study. ese specic groups were included to account for
the age range in the BVP group and to provide an estimation of the eect of ageing alone on the outcome param-
eters. e study was explained before obtaining written informed consent, was conducted in accordance with the
Declaration of Helsinki and was approved by the Maastricht University Medical Centre medical ethics committee
(gait measurements: NL58205.068.16; vestibular tests: NL52768.068.15).
Gait analysis setup, data processing and procedure. e gait measurements were conducted using
the Computer Assisted Rehabilitation Environment Extended (CAREN; Motekforce Link, Amsterdam, e
Netherlands), which includes a dual-belt force plate-instrumented treadmill (Motekforce Link, Amsterdam, e
Netherlands; 1000 Hz), a 12 camera motion capture system (100 Hz; Vicon Motion Systems, Oxford, UK) and a
virtual environment (city-style street with passing objects and structures) projected onto a 180 degrees curved
screen (note that our intention was to provide optic ow for all participants, but aer the rst few measurements
with the BVP group, it became clear that optic ow should be turned o for this group to prevent dizziness and
nausea. e implications for this on the results are discussed in the limitations section). For all measurement
sessions, a safety harness connected to an overhead frame was used. At the request of some of the participants
with BVP, a handrail was also positioned on the treadmill, the use of which was monitored and recorded. Six
retroreective markers were attached to anatomical landmarks (C7, sacrum, le and right trochanter and le
and right hallux) and were tracked by the motion capture system. Marker tracks were ltered using a low pass
second order Butterworth lter (zero-phase) with a 12 Hz cut-o frequency. Foot touchdown was determined
using combined force plate (50 N threshold) and foot marker data25. is combined method was used to be able to
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accurately account for foot touchdowns and toe-os occurring in the center of the treadmill triggering both force
plates simultaneously. For these steps, the foot marker method was used and then corrected based on the average
discrepancy between the force plate method and the marker method timing for all steps that contacted only one
force plate. e spatiotemporal gait parameters of interest were step length (anteroposterior distance between the
hallux markers at foot touchdown), step time (time from touchdown of one foot to touchdown of the next foot),
step width (mediolateral distance between the hallux markers at foot touchdown) and double support time (time
spent with both feet on the ground). Means, standard deviations and coecients of variation (CV) were deter-
mined for each speed for each participant.
Each session began with walking familiarization trials at 0.4 m/s up to 1.6 m/s in 0.2 m/s increments. At least
60 s were used for each speed, and further time was provided to familiarize to each speed if deemed necessary by
either the participant, the CAREN operator or the research clinician. At the end of each speed trial, the decision
to continue to the next (faster) speed was made in a similar manner. If the participant was not comfortable pro-
gressing to the next speed or if the CAREN operator or research clinician did not think it was safe or feasible to
progress, then the participant continued at the current speed instead. Participants were then given sucient rest
before continuing with the measurements. Single two-to-three-minute-long measurements (to ensure a mini-
mum of 60 strides per speed) were then conducted at each prescribed speed that was completed during familiar-
ization. Multiple set walking speeds were used as opposed to the majority of previous studies which have used
either percentages of preferred walking speeds or self-perceived slow, normal and fast walking speeds, in order to
have more control over the walking speed condition.
Clinical vestibular function tests setup and procedures. Following a sucient rest period that was deter-
mined on an individual basis, the BVP group proceeded with the clinical vestibular testing battery. Between each
test, sucient rest was provided based on feedback from the patient and the judgement of the clinical researcher.
The vHIT was performed with the EyeSeeCam system (EyeSeeCam VOG; Munich, Germany) and the ICS
Impulse system (GN Otometrics A/S, Denmark) to test semicircular canal function and determine the gain of the
vestibulo-ocular reex (VOR). Both systems measured the movement of the right eye. e distance of the back of the
static chair was 2 meters to the point of xation. e point of xation consisted of a green dot on the wall, produced
by a laser on a tripod. If necessary, adhesive plasters were used to li the upper eyelid a little to secure the visibility of
the pupil for the camera in all directions. Goggle movement was minimized by adjusting the strap of the goggles to
every subject. e vHIT system was calibrated according to the protocol of the system. Aer calibration, the subject
was instructed to not touch their head including the goggles. e examiner stood behind the participant with two
hands rmly on top of the participants head without touching the strap of the goggles. e examiner then applied
head impulses in six dierent movements to test each canal26. e horizontal head impulses comprised a peak veloc-
ity of >150°/s and the vertical head impulses a peak head velocity of >100°/s. e amplitude of the movements was
10–20°. Only outward impulses were used27. e vHIT was dened as abnormal if the VOR gain was below 0,7 and/
or if covert saccades were observed in 50% or more of the traces26,28.
DVA, which is used to assess gaze stabilization via the VOR during gait-related head movements, was assessed on
a regular treadmill (1210 model, SportsArt, Inc., Tainan, Taiwan, China.) with the participant positioned 2.8 meters
from a computer screen. Firstly, the static visual acuity was determined during stance, followed by the assessment of
the DVA during walking at 2, 4 and 6 km/h. One letter at a time was randomly displayed on the screen from a chart
of Sloan letters (CDHKNORSVZ)29. Starting at a logMAR (log of the Minimum Angle of Resolution30); of 1.0, ve
random letters were shown at each logMAR (decreasing in steps of 0.1 logMAR). When four out of ve letters were
correctly identied, the corresponding logMAR was considered achieved. e outcome of the DVA was the dier-
ence between the static logMAR and the logMAR for each of the three walking speeds. e result was omitted if the
subject needed a handrail to walk at that speed or if it wasn’t possible to walk at that speed at all31.
cVEMP and oVEMP were assessed with the Neuro-Audio system (v2010, Neuroso, Ivanovo, Russia) in order
to determine the function of the otolith organs (saccule and utricle, respectively) and their corresponding nerves. A
monaural stimulation with in-ear earphones was used with air conduction tone bursts at 500 Hz and a stimulation
rate of 13 Hz using a blackman window function with a two-cycle rise/fall and no plateau phase. Tone bursts of max-
imum 130 dB sound pressure level (SPL) were used. A stepwise approach was used to determine the threshold with
a precision of 5 dB SPL32. Positive (P1) and negative (N1) peaks in the recorded biphasic waveform were marked for
both cVEMPs and oVEMPs. e thresholds were determined as the lowest stimulus intensities to elicit recognizable
peaks. If it wasn’t possible to nd a VEMP response, it was dened as a threshold of >130 dB SPL. For the cVEMP,
the participant was positioned lying down with the back positioned at a 30° angle above the horizontal plane and was
asked to turn their head towards the non-measured side and li their head during the measurement. e cVEMP
was recorded at the ipsilateral sternocleidomastoid muscle. Two electrodes were placed on the sternocleidomastoid
muscles, the reference electrode on the sternum, and the earth electrode on the forehead. Electrode impedances
of 5 k or lower were accepted and otherwise the electrode was replaced. To ensure correct muscle contraction, a
feedback system using a screen was provided. An average of 200 EMG traces with a minimum mean rectied voltage
(MRV) of 65µV and a maximum MRV of 205µV was accepted33,34. e oVEMP was recorded at the contralateral
inferior oblique muscle. Five electrodes were used: the recording electrodes beneath the eyelid, just lateral of the
pupil when gazing forward and centrally, the reference electrodes beneath the recording electrode and the earth
electrode on the forehead. e participant was asked to keep their gaze at a focus point placed at a 30 degrees angle
behind the head. An average of at least 300 EMG traces was accepted3537.
Statistics. From the 44 participants with BVP that started the study, 38 participants were able to complete
at least the three slowest walking speeds without assistance (group hereaer referred to as BVP) and these par-
ticipants’ data were taken for the comparison with the healthy groups. For the within BVP comparisons, three
groups were formed. One group was able to complete all of the gait measurements without assistance (BVP All
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Gait; n = 26), the second was only able to complete some of the speeds without assistance (BVP Part Gait; n = 12;
all of this group were able to complete the measurements at least up to 0.8 m/s) and the nal group (BVP No Gait;
n = 6) did not start the recorded gait trials (see “Results” for details on this group).
To investigate the walking speed eects on gait and this eect’s potential interaction with vestibular function,
mixed-eects models using the restricted maximum likelihood method with the xed eects walking speed,
participant group, and speed by group interaction were conducted for the means and CVs of step time and length,
step width and double support time. To further investigate the potential of gait variability to distinguish between
BVP groups, mixed-eects models as described above were applied with groups BVP All Gait and BVP Part Gait
to the CV of all four gait parameters across all speeds that included data points from each group. Bonferroni post
hoc comparisons were performed to assess the group dierences within speeds for each of the gait parameters.
e vHIT testing revealed abnormal canal function in all or most directions for almost all of the participants
with BVP (i.e. exceptions were two participants with BVP who had only one abnormal result out of six). As almost
all outcomes were abnormal and there was no possibility to distinguish between groups, analysis of the vHIT
results in relation to gait was not taken further. For all completed DVA trials with a logMAR change value during
the three walking speeds compared to standing and when oVEMP or cVEMP thresholds were detected, these val-
ues were grouped and Pearson correlations with the gait parameters that showed highest variability and/or distin-
guished between BVP groups were conducted (see Results). Age, height, weight and body mass index (BMI) were
compared across the participant groups BVP, Young and Older, and within the three BVP groups (BVP All Gait,
BVP Part Gait, BVP No Gait) using one-way ANOVAs with Bonferroni corrections for multiple comparisons.
Results
Twenty-six participants with BVP were able to complete all of the gait measurements without assistance (BVP All
Gait). Twelve participants with BVP were only able to complete some of the speeds (BVP Part Gait), of which one
participant stopped aer 0.8 m/s, one aer 1.0 m/s, four aer 1.2 m/s and six aer 1.4 m/s. Six participants with
BVP were assigned to the BVP No Gait group for the following reasons: one participant became dizzy and nause-
ated during familiarization and could not continue; three participants were not able to walk during familiarization
without handrail support; two participants found treadmill walking too challenging and could not continue. e
demographic data of these three groups, as well as the healthy control group can be found in Table1. e one-way
ANOVAs revealed a signicant group eect (BVP, Young, Older) for age (F (2,59) = 88), P < 0.0001), with age signif-
icantly diering between each of the groups (P < 0.0001). Height, weight and BMI did not signicantly dier across
these groups. No signicant dierences in demographics were found with the three BVP groups.
e mixed-eects models with walking speed (0.4 to 1.6 m/s) and group (BVP, Young, Older) as factors
revealed signicant walking speed eects for the means and CV of step time and length, step width and double
support time (P 0.0003), signicant group eects for all parameters except step width means (P 0.0151) and
signicant walking speed by group interactions for the means of step time, double support time and step width
(P 0.0053) and the CV of step width (P < 0.0001). e mixed-eects model results and summary of the between
group Bonferroni comparisons are displayed in Fig.1 (means) and Fig.2 (CVs), and the full Bonferroni compar-
ison results are available in Supplementary Tables1 and 2.
e mixed-eects models with walking speed (0.4 to 1.4 m/s) and group (BVP All Gait and BVP Part Gait)
as factors revealed signicant walking speed eects for the CV of all parameters (P < 0.0001). Signicant group
eects were found for the CV of step time, step length and double support time (P 0.0162) and a signicant
walking speed by group interaction was found for the CV of double support time (P = 0.0172). e mixed-eects
model results and summary of the between group Bonferroni comparisons are displayed in Fig.3 and the full
Bonferroni comparison results are available in Supplementary Table3.
When cVEMP and oVEMP thresholds were detected, and when a speed of the DVA was completed, these
values were taken and Pearson correlations were conducted with the CVs of step time, step length and double
support time at 0.4 m/s and the CV of step width at 1.6 m/s, being the speeds with the highest variability in those
parameters from the previous analysis. ese results can be seen in Table2. Only two signicant correlation of 28
were found (change in logMAR scores during the DVA with Double Support CV at 6 km/h and oVEMP Le and
Step Length CV at 0.4 m/s; Table2).
Post-hoc analysis of gait data based on VEMP results. In order to further investigate dierences
within the patient group, we conducted an analysis of the gait data of the participants with and without at least
one detected VEMP threshold for the same four parameters as the correlations: the CVs of step time, step length
and double support time at 0.4 m/s and the CV of step width at 1.6 m/s. Given that all of the participants with no
nAge (y) Height (cm) Weight (kg) Body Mass Index
Young 12 (7 female) 25.1 ± 2.8*174.9 ± 7.3 72.6 ± 13.5 23.6 ± 2.8
Older 12 (4 female) 71.5 ± 4.8*171.5 ± 9.1 79.5 ± 11.8 26.9 ± 2.2
BVP 38 (20 female) 56.1 ± 11*174.6 ± 10.1 80.2 ± 17.6 26.1 ± 4.2
BVP All Gait 26 (10 female) 55.1 ± 11.4 176.8 ± 9.9 80.3 ± 17.8 25.4 ± 3.8
BVP Part Gait 12 (10 female) 59.2 ± 9 169.7 ± 9 79.9 ± 18 27.6 ± 4.7
BVP No Gait 6 (2 female) 65.3 ± 13.6 174 ± 6.9 82.4 ± 13.4 27.2 ± 3.8
Table 1. Participant Group Characteristics. Values are means ± SD. *Signicantly dierent from each other
(P < 0.0001).
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VEMP threshold detected also had abnormal outcomes on the vHIT for most or all of the six directions tested,
the purpose of this analysis was to compare the gait of participants with and without detectable canal and otolith
function. Independent samples t-tests with Welch’s corrections did not reveal any signicant dierences between
the participants with and without at least one detectable VEMP threshold (0.0965 < P < 0.746).
0.0
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
1.1
1.2
Step Time [s]
BVP
Young
Older
0.00
0.05
0.10
0.15
0.20
0.25
0.30
0.35
0.40
0.45
Double SupportTime[s]
0.40.6 0.81.0 1.21.4 1.6
0.00
0.05
0.10
0.15
0.20
0.25
0.30
0.35
0.40
Walking Speed [m/s]
Step Width[m]
0.0
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
Step Length [m]
SpeedP<0.0001F (1.364, 75.46) = 564.4
GroupP=0.0012F (2, 59) = 7.564
Interaction P<0.0001F (12, 332) = 5.744
SpeedP<0.0001F (2.127, 117.7) = 2460
GroupP=0.0008F (2, 59) = 8.039
Interaction P=0.5116F (12, 332) = 0.9353
SpeedP<0.0001F (1.327, 73.43) = 743.4
GroupP=0.0151F (2, 59) = 4.503
Interaction P<0.0001F (12, 332) = 7.047
SpeedP=0.0003F (2.338, 129.4) = 7.909
GroupP=0.3964F (2, 59) = 0.9400
Interaction P=0.0053F (12, 332) = 2.410
Figure 1. Boxplots of the median, interquartile range and 5th and 95th percentile of the means of step time,
step length, double support time and step width across all conducted walking speeds in BVP, Young and Older
participant groups. e black horizontal lines indicate signicant between group dierences for the indicated
speed (P < 0.05, Bonferroni adjusted).
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Discussion
We aimed to determine the eects of systematic increases in walking speed on spatiotemporal gait parameters and
their variability in people with BVP. We investigated if these parameters would distinguish between healthy par-
ticipants and participants with BVP, and between patients with BVP who could and could not complete all of the
planned walking speed trials (a simple proxy of locomotor capacity). Our hypothesis, that step and double sup-
port time and step length variability would systematically reduce with increases in walking speed, whereas step
0
2
4
6
8
10
12
Step Time CV [%]
BVP
Young
Older
0
4
8
12
16
Step Length CV [%]
0
10
20
30
40
Double SupportTimeCV[%]
0.40.6 0.81.0 1.21.4 1.6
0
20
40
60
80
Walking Speed [m/s]
Step WidthCV[%]
Speed P<0.0001 F (2.323, 128.5) = 141.2
GroupP=0.0122 F (2, 59) = 4.755
InteractionP=0.7565F (12, 332) = 0.6949
Speed P<0.0001F (2.531, 140.0) = 162.1
GroupP=0.0007F (2, 59) = 8.316
Interaction P=0.3897 F (12, 332) = 1.064
Speed P<0.0001 F (3.321, 183.7) = 42.59
GroupP=0.0033 F (2, 59) = 6.305
InteractionP=0.8176F (12, 332) = 0.6288
Speed P<0.0001 F (3.039, 168.2) = 22.06
GroupP=0.0011 F (2, 59) = 7.718
Interaction P<0.0001 F (12, 332) = 7.006
Figure 2. Boxplots of the median, interquartile range and 5th and 95th percentile of the coecients of variation
(CV) of step time, step length, double support time and step width across all conducted walking speeds in BVP,
Young and Older participant groups. e black horizontal lines indicate signicant between group dierences
for the indicated speed (P < 0.05, Bonferroni adjusted).
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width variability would systematically increase, was conrmed as signicant walking speed eects were found for
all gait variability parameters. We additionally hypothesized that step and double support time and step length
variability at slower walking speeds would be most distinguishing between the healthy control participants and
patients with BVP, and also between the patients with BVP that could completely and only partially complete
the measurement protocol, whereas step width variability would be most distinguishing between these groups at
faster walking speeds. is hypothesis was partly conrmed; step length CV diered between groups BVP and
0
2
4
6
8
10
12
Step Time CV [%]
BVP All Gait
BVP Part Ga
it
0
5
10
15
20
Step Length CV [%]
0
10
20
30
40
Double SupportTimeCV[%]
0.40.6 0.81.0 1.
21
.4
0
20
40
60
80
Walking Speed [m/s]
Step WidthCV[%]
Speed P<0.0001 F (2.474, 84.61) = 113.0
GroupP=0.0162 F (1, 36) = 6.358
InteractionP=0.0663F (5, 171) = 2.112
Speed P<0.0001 F (2.963, 101.3) = 116.3
GroupP=0.0037 F (1, 36) = 9.625
InteractionP=0.0172 F (5, 171) = 2.840
Speed P<0.0001 F (3.010, 102.9) = 32.73
GroupP=0.0073 F (1, 36) = 8.078
InteractionP=0.3285F (5, 171) = 1.165
SpeedP<0.0001F (1.528, 52.25) = 43.54
Group P=0.5427 F (1, 36) = 0.3778
Interaction P=0.0 523F (5, 171) = 2.242
Figure 3. Boxplots of the median, interquartile range and 5th and 95th percentile of the coecients of variation
(CV) of step time, step length, double support time and step width across all walking speeds with data from
participant groups BVP All Gait and BVP Part Gait. e black horizontal lines indicate signicant between
group dierences for the indicated speed (P < 0.05, Bonferroni adjusted).
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Young and between groups BVP All Gait and BVP Part Gait, double support time CV diered between groups
BVP and Young and step width CV diered between groups BVP and Young and BVP and Older for step width
variability, but other parameters did not signicantly dier at the pairwise comparison level, despite the group
eects found for all parameters except step width CV in the BVP All Gait vs. BVP Part Gait analysis.
Regarding our explorative analysis in the patient groups examining correlations between the outcomes of four
clinical vestibular tests (vHIT, oVEMP, cVEMP, DVA) and the most distinguishing gait parameters identied, only
one signicant correlation between the change in logMAR scores during the DVA and the gait parameters were
found (6 km/h and Double Support CV; Table2). One signicant correlation of 16 was found between the VEMP
thresholds and the gait parameters, but only nine pairs of data were included in this test and if a Bonferroni correc-
tion is made for the p values of these 16 tests, it is no longer signicant (oVEMP Le and Step Length CV at 0.4 m/s;
Table2). Similarly, the one signicant correlation between a DVA parameter and gait variability (DVA 6 km/h and
Double support time CV 0.4 m/s) does not meet the signicance threshold if a Bonferroni correction for the 12 tests
is made. Even though this study clearly demonstrates the signicant contribution of vestibular function to gait, our
exploratory analysis conrms the complex contribution of vestibular information during every-day activities and the
diculty in translating current objective clinical measures to highly relevant patient symptoms.
Determining meaningful and distinguishing gait parameters in BVP is vital for the development of interventions,
as is using tasks that suciently replicate the day-to-day challenges of these patients, to determine candidates for inter-
vention and to assess the eect of those interventions. Two promising interventions currently under development and
investigation include noisy galvanic vestibular stimulation (nGVS) and vestibular implants16,17,3840. Discussions of
these treatment options can be found elsewhere16,38, but it is important to note that both show early signs of utility for
improving gait in BVP4,41. However, it remains to be seen if improvement due to nGVS or a vestibular implant in steady
state gait would likewise be seen in more dynamic locomotor task performance, where even unilateral vestibulopathy
leads to signicantly poorer stability performance42. It should be noted that while this study examined spatiotemporal
variability, dierences in dynamic gait stability were not directly assessed and the two are not necessarily equivalent4345.
e parameters presented here represent the amount of variability in the gait parameters, but do not necessarily indicate
the overall stability of the participants. erefore, future work should investigate how dynamic gait stability is altered
in BVP and how this is aected by changes in walking speed. Additionally, we suggest that quantication of vestibu-
lospinal reexes and reex gains associated with gait stability control in BVP should be conducted, in order to better
understand the underlying mechanisms of changes in gait stability in vestibulopathy.
Step Time CV 0.4 m/s Step Length CV 0.4 m/s Double Support Time CV 0.4 m/s Step Width CV 1.6 m/s
cVEMP
Right
r 0.08987 0.3259 0.2576 0.3501
95% CI 0.3935 to 0.5343 0.1662 to 0.6881 0.2379 to 0.6467 0.7554 to 0.2489
P (two-tailed) 0.7229 0.1868 0.302 0.241
n 18 18 18 13
cVEMP
Le
r0.2425 0.1195 0.1732 0.5043
95% CI 0.659 to 0.2878 0.3999 to 0.5808 0.616 to 0.3528 0.8362 to 0.09795
P (two-tailed) 0.3655 0.6595 0.5212 0.0945
n 16 16 16 12
oVEMP
Right
r 0.4653 0.561 0.286 0.4649
95% CI 0.7074 to 0.9554 0.6361 to 0.9654 0.7975 to 0.9329 0.7076 to 0.9553
P (two-tailed) 0.4297 0.3251 0.6408 0.4301
n 5 5 5 5
oVEMP
Le
r0.04995 0.7914 0.08001 0.3605
95% CI 0.6911 to 0.6352 0.2684 to 0.9541 0.6169 to 0.7066 0.8494 to 0.4614
P (two-tailed) 0.8985 0.0111 0.8379 0.3803
n 9 9 9 8
DVA
2 km/h
r0.1244 0.01669 0.2151 0.09623
95% CI 0.4271 to 0.2034 0.3046 to 0.3346 0.5004 to 0.1123 0.4662 to 0.3024
P (two-tailed) 0.4568 0.9208 0.1947 0.6401
n 38 38 38 26
DVA
4 km/h
r 0.06088 0.1711 0.03413 0.2422
95% CI 0.2639 to 0.3733 0.4654 to 0.1572 0.2887 to 0.35 0.1602 to 0.5756
P (two-tailed) 0.7166 0.3043 0.8388 0.2332
n 38 38 38 26
DVA
6 km/h
r0.3145 0.3199 0.4338 0.06129
95% CI 0.6371 to 0.1018 0.6406 to 0.09588 0.7125 to 0.0369 0.4803 to 0.3805
P (two-tailed) 0.1345 0.1275 0.0342 0.7918
n 24 24 24 21
Table 2. Pearson correlations between the cVEMP and oVEMP thresholds, the change in logMAR scores
during each of the three DVA walking speeds and the gait parameters.
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e current study conrmed previous ndings of reductions in temporal gait variability and reductions in
sagittal plane spatial gait variability in vestibulopathy during faster, compared to slower walking24. We extend
these previous ndings as the current study employed xed (not self-selected) speeds that were systematically
increased, with 120 steps analyzed per speed, thereby improving the reliability of the outcomes. Our ndings also
align with the growing body of literature indicating a shi from sensory feedback-driven balance control to an
increasingly feedforward control with increasing locomotor speed1,18,22,23,46, but suggest that this may not apply,
at least not to the same extent, for mediolateral balance control during gait which may continue to require active
control of foot placement in the mediolateral plane. Importantly, the current results further the previous ndings
by additionally showing that these parameters are related to the locomotor capacities of people with BVP.
We conrmed previously reported increases in step width variability with increasing walking speeds in people
with BVP4. Previous studies have shown that vestibular perturbations have less impact on direction and variabil-
ity at higher walking speeds20,21 and that the vestibular inuence on lower limb muscles is selectively suppressed
with increased cadence and speed during walking22,23. However, the current step width variability results, com-
bined with those ofWuehr, et al.4 suggest that vestibular information remains important for mediolateral foot
placement at increased walking speeds. During the swing phase when foot placement is coordinated and deter-
mined, there is reduced proprioceptive input due to only one foot being in contact with the ground. erefore,
we could reason that vestibular input becomes more important in this phase, and disturbed or lacking vestibular
input may decrease foot placement accuracy. ese results also provide some explanation as to why people with
BVP do not self-select walking speeds that minimize temporal or sagittal plane spatial gait variability24. Dramatic
increases in step width variability may be undesirable due to reduced stability control or increased energetic costs
of mediolateral stabilization4749. Based on the current results, either reason is plausible, as some participants in
the BVP Part Gait group did not continue to the faster speeds due to instability, while others could not continue
due to being unable to keep up with the speed of the treadmill (implying an energetic or physiological limitation,
not a stability-related one). e vestibular inuence on gait economy has not yet been thoroughly investigated.
e healthy control groups in this study were not directly age matched with the BVP group, but rather repre-
sent healthy participants at the younger and older end of the age range of the BVP group. Variability in step time,
double support time and step length of the older group tended to fall between that of the younger and BVP group,
showing few statistical dierences to either (probably due to a lack of statistical power at the pairwise comparison
level). e boxplots seem to indicate that the group Older tend towards the results of group Young for double sup-
port time and step length variability. In order to further investigate this issue, we calculated the Cohens d eect
sizes for each group comparison (Young vs. Older, Young vs. BVP and Older vs. BVP) and averaged these across
the walking speeds for Step Time CV (0.65, 0.98, 0.39), Step Length CV (0.95, 1.31, 0.60), Double Support Time
CV (0.58, 1.00, 0.50) and Step Width CV (0.21, 1.04, 0.84). ese eect sizes conrm that the largest dierences
were always between the Young and BVP groups, but that the dierences between the Older and BVP groups were
also always moderate to large, even if not statistically signicant, indicating that while age may have been a factor
in the Young-BVP comparisons, it certainly does not explain the dierences found. However, the group dier-
ence in step width variability appear to be more robust, with large signicant dierences between the BVP group
and each healthy group, and no dierence due to healthy ageing alone, in agreement with previous studies50,51.
However, other limitations should be kept in mind. Firstly, we did not perform any tests of somatosensory func-
tion in the older adult group, and while we think our inclusions criteria “no history of balance or gait diculties
and no history of dizziness” probably deemed somatosensory dysfunction unlikely, it cannot be entirely ruled out.
We did however perform the DVA and vHIT tests with nine and eight out of 12 older participants, respectively,
which revealed normal function (due to equipment issues, the remaining older adults were not assessed on these
tests). Regarding the gait results, we caution comparing the CV of step width to studies of overground walking, as
it has been shown in healthy participants that walking on the CAREN results in increased step width variability
compared to overground walking52. Additionally, the use of a safety harness may result in small dierences to
unconstrained overground gait53. Furthermore, treadmill walking appears to be more challenging for people with
BVP, evidenced by the fact that the BVP No Gait group were not able to successfully complete the familiarization
period, despite reporting being able to walk independently without assistance. We would therefore caution a
direct comparison of treadmill-derived gait results with overground gait results in BVP. It should also be noted
that the walking speeds used in the current study were not randomized, but progressed from slow to fast, and this
could have led to an order eect. We hope that this was minimized by our familiarization protocol, but it cannot
be ruled out. is should not have aected our comparisons, however, as all participants followed the same pro-
tocol. Minor fatigue may have occurred during the assessments, but this should have been minimized as the par-
ticipants were monitored and breaks were provided when necessary. Regarding the fact that the healthy groups
walked with optic ow and the BVP group walked with the virtual environment xed (so as to provide the same
lighting), we do not expect that this dierence would have altered our results, as two previous studies found no,
or negligible, dierences in the parameters assessed here between xed speed walking with and without virtual
reality54,55. e only previous study that did nd dierences in gait variability due to virtual reality that we are
aware of is that of Hollman, et al.56. However, Hollman, et al.56 used an insucient number of data points to reli-
ably assess gait variability55 and used a substantially dierent virtual reality setup to the current study. Finally, the
eect sizes of the dierence in step width variability with and without virtual reality and optic ow from Hollman,
et al.56 are much smaller than those found in the current study between Young and BVP All Gait groups at similar
walking speeds (Cohen’s d of 0.238–0.657 in Hollman, et al.56 vs. 1.064–1.382 in the current study).
We also acknowledge that our division of participants into the BVP All Gait and BVP Part Gait groups is based
on a rather simple criterion. Of the 12 participants in the BVP Part Gait group, the range of locomotor capacities
within this group is likely broad. Reasons for lack of completion also varied across the participants, with some
stopping due to lack of stability control (too much lateral deviation with a risk of stepping o the treadmill)
and others unable to keep up with a faster belt speed. Nevertheless, we found signicant group eects on gait
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variability, indicating the potential association between gait variability and overall locomotor capacity in BVP.
Further research into gait parameters that can distinguish between patients with dierent functional limitations
is encouraged to aid the development of accurate diagnostic functional testing protocols.
In conclusion, spatiotemporal gait parameters and their variability show speed-dependency in people with
BVP and in healthy adults. In particular, step length variability at slower speeds and step width variability at faster
speeds were the most distinguishing parameters between the healthy participants and people with BVP, and
within groups with BVP who have dierent locomotor capacities. Gait variability in BVP was generally not corre-
lated with the clinical tests of vestibular function. e current ndings indicate that analysis of gait variability at
multiple speeds has potential as an assessment tool for vestibular interventions.
Data availability
e datasets generated during and analysed during the current study are available from the corresponding author
on reasonable request.
Received: 15 August 2019; Accepted: 13 November 2019;
Published: xx xx xxxx
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Acknowledgements
e authors thank Wouter Bijnens, Rachel Senden and Rik Marcellis for their support with the measurements.
CM was funded by the Kootstra Talent Fellowship awarded by the Centre for Research Innovation, Support and
Policy (CRISP) and by the NUTRIM Graduate Programme, both of Maastricht University Medical Center+. FL
was nancially supported by MED-EL. RvdB and HK were supported in part by the Russian Science Foundation
(Project No. 17-15-01249).A pre-print version of this work is available at bioRxiv57.
Author contributions
Conception of the study: C.M., R.v.d.B., K.K., H.K. and K.M. Data Collection: C.M. and F.L. Data Analysis: C.M.,
P.W. and F.L. Interpreted results: All authors. Prepared Figures: C.M. Draed the article: C.M. Reviewed and
revised the article: All authors. Approved nal version: All authors.
Competing interests
e authors declare no competing interests.
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... Bilateral vestibulopathy (BVP), categorized by significant bilateral impairment or absence of vestibular function, 1,2 leads to various physical, cognitive and emotional complaints, often contributing to a diminished quality of life. 3 Among these complaints, reduced balance performance, 4,5 an increased risk of falls, [6][7][8][9] and increased variability of spatiotemporal gait parameters 8,10,11 can severely affect patients' mobility. Clinical tests of vestibular function do not correspond well to increased risk of falls 8,12 or to spatiotemporal gait variability parameters in people with BVP, 10 indicating that tests of gait and balance are an important addition to vestibular function testing. ...
... 3 Among these complaints, reduced balance performance, 4,5 an increased risk of falls, [6][7][8][9] and increased variability of spatiotemporal gait parameters 8,10,11 can severely affect patients' mobility. Clinical tests of vestibular function do not correspond well to increased risk of falls 8,12 or to spatiotemporal gait variability parameters in people with BVP, 10 indicating that tests of gait and balance are an important addition to vestibular function testing. However, gait analysis can be costly, time consuming and require specific expertise and equipment. ...
... In our previous study, we found that step length, step time and double support time variability could distinguish between the healthy participants and participants with BVP, and between people with BVP with different locomotor capacities. 10 In a previous study, people with bilateral vestibulopathy completed a dynamic visual acuity test on a treadmill. 12 While not analysed or reported in the previous publication, motion capture data was recorded during most of these trials. ...
Article
Full-text available
Background. Gait variability is increased in people with bilateral vestibulopathy (BVP). Since dedicated gait analysis can be resource-intensive, concurrent assessment with another vestibular function test, dynamic visual acuity (DVA), is worth consideration. Objective. To assess comparability of results from a combined gait and DVA assessment with results from a previous dedicated gait analysis. Methods. 15 participants (4 women) with BVP were analysed. The DVA test assessed visual acuity during stance and during treadmill walking at 2, 4 and 6 km/h. An 8-camera motion capture system measured spatiotemporal gait parameters (step length, step time, step width and double support time; means and coefficients of variation [CoV]). The walking speed effect was assessed by mixed-effects models, and results were visually compared to previous results. Results. Walking speed affected the means of step length, step time and double support time (p < .0001) but not step width (p = .373) and significantly affected the CoV of all parameters (p < .01). These values, as well as speed-related changes, were comparable between contexts. Conclusions. Concurrent DVA and gait assessment seems promising as an assessment method in people with BVP. Test-retest reliability, clinically feasible motion capture solutions and sensitivity to change following interventions should be further investigated.
... Bilateral vestibulopathy (BVP), categorised by significant bilateral impairment or absence of vestibular function [1,2], leads to various physical, cognitive, and emotional complaints, often contributing to a diminished quality of life [3]. Among these complaints, reduced balance performance [4,5], an increased risk of falls [6][7][8][9] and increased variability of spatiotemporal gait parameters [8,10,11] can severely affect patients' mobility. Clinical tests of vestibular function do not correspond well to increased risk of falls [8,12] or to spatiotemporal gait variability parameters in people with BVP [10], indicating that tests of gait and balance are an important addition to vestibular function testing. ...
... Among these complaints, reduced balance performance [4,5], an increased risk of falls [6][7][8][9] and increased variability of spatiotemporal gait parameters [8,10,11] can severely affect patients' mobility. Clinical tests of vestibular function do not correspond well to increased risk of falls [8,12] or to spatiotemporal gait variability parameters in people with BVP [10], indicating that tests of gait and balance are an important addition to vestibular function testing. However, gait analysis can be costly, time consuming and require specific expertise and equipment. ...
... However, due to differences in task duration (and thereby number of steps measured) and requirements (e.g., concurrent walking and DVA assessment may function as a cognitive dual-task and could lead to deteriorations in gait [18,19]), it is currently unclear if mean and variability values of spatiotemporal gait parameters assessed during DVA testing will closely replicate previous values found in more dedicated gait analysis setups and protocols. In our previous study, we found that step length, step time and double support time variability could distinguish between the healthy participants and participants with BVP, and between people with BVP with different locomotor capacities [10]. ...
Preprint
Full-text available
BACKGROUND: Gait variability is increased in people with bilateral vestibulopathy (BVP). Since dedicated gait analysis can be resource intensive, concurrent assessment with another vestibular function test, dynamic visual acuity (DVA), is worth consideration. OBJECTIVE: To assess comparability of results from a combined gait and DVA assessment with results from a previous dedicated gait analysis. METHODS: 15 participants (4 women) with BVP were analysed. The DVA test assessed visual acuity during stance and during treadmill walking at 2, 4, and 6 km/h. An 8-camera motion capture system measured spatiotemporal gait parameters (step length, step time, step width and double support time; means and coefficients of variation (CoV)). The walking speed effect was assessed by mixed effects models and results were visually compared to previous results. RESULTS: Walking speed affected the means of step length, step time and double support time (P<0.0001) but not step width (P=0.373) and significantly affected the CoV of all parameters (P<0.01). These values, as well as speed-related changes, were comparable between contexts. CONCLUSIONS: Concurrent DVA and gait assessment seems promising as an assessment method in people with BVP. Test-retest reliability, clinically feasible motion capture solutions and sensitivity to change following interventions should be further investigated.
... Most research on the analysis of movement in patients with vestibulopathy has focused on spatiotemporal parameters [13][14][15][16][17] , which simply describe the general characteristics of the gait pattern (e.g. walking speed, step length, step time, etc.). ...
... Indeed, kinematic curves enable detailed analysis of angular variations at the various joint or body segments concerned 19 . Furthermore, researchers have investigated either unilateral 11,13,14,17,20,21 or bilateral 15,22 vestibulopathy, but very few comparisons exist between these two groups 23 . We believe it is important to characterise and compare these pathological groups to obtain relevant outcomes for evaluating new treatments. ...
... Moreover, several studies have shown that the dispersion of sample values and the variability of the data provide instructive information for a better understanding of the walking and balance difficulties encountered by vestibulopathy patients 14,15,24 . McCrum et al. 15 suggested that the analysis of the variability of walking can be used as an assessment tool for vestibular interventions. ...
Article
Full-text available
Chronic imbalance is a frequent and limiting symptom of patients with chronic unilateral and bilateral vestibulopathy. A full-body kinematic analysis of the movement of patients with vestibulopathy would provide a better understanding of the impact of the pathology on dynamic tasks such as walking. Therefore, this study aimed to investigate the global body movement during walking, its variability (assessed with the GaitSD), and the strategies to stabilise the head (assessed with the head Anchoring Index). The full-body motion capture data of 10 patients with bilateral vestibulopathy (BV), 10 patients with unilateral vestibulopathy (UV), and 10 healthy subjects (HS) walking at several speeds (slow, comfortable, and fast) were analysed in this prospective cohort study. We observed only a few significant differences between groups in parts of the gait cycle (shoulder abduction–adduction, pelvis rotation, and hip flexion–extension) during the analysis of kinematic curves. Only BV patients had significantly higher gait variability (GaitSD) for all three walking speeds. Head stabilisation strategies depended on the plan of motion and walking speed condition, but BV and UV patients tended to stabilise their head in relation to the trunk and HS tended to stabilise their head in space. These results suggest that GaitSD could be a relevant biomarker of chronic instability in BV and that the head Anchoring Index tends to confirm clinical observations of abnormal head-trunk dynamics in patients with vestibulopathy while walking.
... In particular the unsteadiness can be difficult to recognize as balance control is a multisensory process (31)(32)(33). Compensation via sensory reweighting plays a key role in attempted recovery from BVP. In this process, the remaining senses such as vision, somatosensory input (e.g., pressure perception) and proprioception are preferentially utilized (34). ...
... However, BVP patients do tend to walk with an increased cadence (35). When testing gait at fixed walking speeds, gait parameters such as step length and step width variability differ significantly to those of healthy controls (33). Sensory reweighting also explains why certain complaints worsen in situations where other sensory inputs are less effective, such as worsening of unsteadiness in poorly lit environments. ...
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Full-text available
Bilateral vestibulopathy (BVP) is characterized by its heterogeneous and chronic nature with various clinical presentations and multiple etiologies. This current narrative review reflects on the main insights and developments regarding clinical presentation. In addition, it proposes a new diagnostic algorithm, and describes available and potential future therapeutic modalities.
... About 30-40% of people with BVP suffer from oscillopsia during head motion, due to reduced or absent vestibular-ocular reflex (VOR) [3]. In addition, people with BVP have a higher risk of falls [4], increased gait variability [5,6] and often report difficulty and instability while walking in dimly lit environments and on uneven ground [7][8][9]. Consequently, avoidance of falls and reduction in mobility may occur and negatively impact societal participation, which may be linked with the increase in depression and reduced quality of life in people with vestibular disorders [10][11][12][13][14][15]. ...
... Deficient vestibular function may be defined using video head impulse testing (vHITs), caloric testing and torsion swing test and evaluation of dynamic visual acuity (DVA), cervical and ocular vestibular-evoked myogenic potentials for otolith function and Romberg testing for balance [1,16,17]. However, McCrum et al. [6] found no clear correlation between various gait variability parameters and the results of the caloric, vHIT and DVA tests, indicating that specific, objective assessment of balance and gait may be required in BVP to gain a better picture of a patient's deficits. ...
Article
Full-text available
Objectives Bilateral vestibulopathy (BVP) leads to unsteadiness when walking, which worsens in darkness or on uneven ground, as well as falls. Since simple balance tests struggle to distinguish between BVP and healthy participants, we aimed (1) to test if the Mini-BESTest is feasible in BVP, (2) how people with BVP perform on the Mini-BESTest and (3) to compare these scores with healthy reference data. Methods Fifty participants with BVP completed the Mini-BESTest. 12-month falls incidence was obtained by questionnaire. To compare the overall and sub-scores between our participants with BVP and those of healthy participants from the literature (n = 327; obtained via PubMed searches), Mann–Whitney U tests were used. Sub scores within the BVP group were also compared. Spearman correlations were used to investigate the relationships between Mini-BESTest score and age. Results No floor or ceiling effects were observed. Participants with BVP had significantly lower Mini-BESTest total scores than the healthy group. Anticipatory, reactive postural control and sensory orientation sub scores of the Mini-BESTest were significantly lower in BVP, while dynamic gait sub scores were not significantly different. A stronger negative correlation between age and Mini-BESTest total score was found in BVP than in the healthy group. Scores did not differ between patients with different falls history. Conclusion The Mini-BESTest is feasible in BVP. Our results confirm the commonly reported balance deficits in BVP. The stronger negative association between age and balance in BVP might reflect the age-related decline in the remaining sensory systems with which people with BVP compensate.
... Particularly, quadrupedal animals with vestibular lesions experience balance impairments and exhibit a shorter swing duration and variability in foot placement [94]. It was shown that genetic suppression of vestibular circuits has profound effects on locomotion. ...
Article
Full-text available
Locomotion is a complex process involving specific interactions between the central neural controller and the mechanical components of the system. The basic rhythmic activity generated by locomotor circuits in the spinal cord defines rhythmic limb movements and their central coordination. The operation of these circuits is modulated by sensory feedback from the limbs providing information about the state of the limbs and the body. However, the specific role and contribution of central interactions and sensory feedback in the control of locomotor gait and posture remain poorly understood. We use biomechanical data on quadrupedal locomotion in mice and recent findings on the organization of neural interactions within the spinal locomotor circuitry to create and analyse a tractable mathematical model of mouse locomotion. The model includes a simplified mechanical model of the mouse body with four limbs and a central controller composed of four rhythm generators, each operating as a state machine controlling the state of one limb. Feedback signals characterize the load and extension of each limb as well as postural stability (balance). We systematically investigate and compare several model versions and compare their behaviour to existing experimental data on mouse locomotion. Our results highlight the specific roles of sensory feedback and some central propriospinal interactions between circuits controlling fore and hind limbs for speed-dependent gait expression. Our models suggest that postural imbalance feedback may be critically involved in the control of swing-to-stance transitions in each limb and the stabilization of walking direction.
... Gait analysis will be conducted on a dual-belt force plate-instrumented treadmill on a motion platform using motion capture and accelerometer data. Participants will walk unperturbed and perturbed (continuous, pseudorandom mediolateral platform sways) at multiple speeds (0.6m/s, 0.8m/s and 1.0m/s) similar to our previous work [51]. The primary parameters of interest are the coefficients of variation of step length, step time, step width and double support time. ...
Article
Full-text available
Background A combined vestibular (VI) and cochlear implant (CI) device, also known as the vestibulocochlear implant (VCI), was previously developed to restore both vestibular and auditory function. A new refined prototype is currently being investigated. This prototype allows for concurrent multichannel vestibular and cochlear stimulation. Although recent studies showed that VCI stimulation enables compensatory eye, body and neck movements, the constraints in these acute study designs prevent them from creating more general statements over time. Moreover, the clinical relevance of potential VI and CI interactions is not yet studied. The VertiGO! Trial aims to investigate the safety and efficacy of prolonged daily motion modulated stimulation with a multichannel VCI prototype. Methods A single-center clinical trial will be carried out to evaluate prolonged VCI stimulation, assess general safety and explore interactions between the CI and VI. A single-blind randomized controlled crossover design will be implemented to evaluate the efficacy of three types of stimulation. Furthermore, this study will provide a proof-of-concept for a VI rehabilitation program. A total of minimum eight, with a maximum of 13, participants suffering from bilateral vestibulopathy and severe sensorineural hearing loss in the ear to implant will be included and followed over a five-year period. Efficacy will be evaluated by collecting functional (i.e. image stabilization) and more fundamental (i.e. vestibulo-ocular reflexes, self-motion perception) outcomes. Hearing performance with a VCI and patient-reported outcomes will be included as well. Discussion The proposed schedule of fitting, stimulation and outcome testing allows for a comprehensive evaluation of the feasibility and long-term safety of a multichannel VCI prototype. This design will give insights into vestibular and hearing performance during VCI stimulation. Results will also provide insights into the expected daily benefit of prolonged VCI stimulation, paving the way for cost-effectiveness analyses and a more comprehensive clinical implementation of vestibulocochlear stimulation in the future. Trial registration ClinicalTrials.gov: NCT04918745. Registered 28 April 2021.
Preprint
Full-text available
Locomotion is a complex process involving specific interactions between the central neural controller and the mechanical components of the system. The basic rhythmic activity generated by locomotor circuits in the spinal cord defines rhythmic limb movements and their central coordination. The operation of these circuits is modulated by sensory feedback from the limbs providing information about the state of the limbs and the body. However, the specific role and contribution of central interactions and sensory feedback in the control of locomotor gait and posture remain poorly understood. We use biomechanical data on quadrupedal locomotion in mice and recent findings on the organization of neural interactions within the spinal locomotor circuitry to create and analyze a tractable mathematical model of mouse locomotion. The model includes a simplified mechanical model of the mouse body with four limbs and a central controller composed of four rhythm generators, each operating as a state machine controlling the state of one limb. Feedback signals characterize the load and extension of each limb as well as postural stability (balance). We systematically investigate and compare several model versions and compare their behavior to existing experimental data on mouse locomotion. Our results highlight the specific roles of sensory feedback and some central propriospinal interactions between circuits controlling fore and hind limbs for speed-dependent gait expression. Our models suggest that postural imbalance feedback may be critically involved in the control of swing-to-stance transitions in each limb and the stabilization of walking direction.
Article
Full-text available
Noisy galvanic vestibular stimulation (nGVS) can boost vestibular sensory thresholds via stochastic resonance and research on nGVS as an intervention for vestibulopathy has accelerated recently. Recent research has investigated the effects and associated mechanisms of nGVS on balance and gait. nGVS has potential as an intervention for balance and gait-related deficits in vestibulopathy, but further research into the mechanisms underlying these effects and consensus on stimulation protocols are required.
Preprint
Full-text available
Study of balance and gait deficits associated with vestibulopathy is important for improving clinical care and is critical to our understanding of the vestibular contributions to gait and balance control. Previous studies report a speed-dependency of the vestibular contributions to gait, so we examined the walking speed effects on gait variability in healthy young and older adults and in adults with bilateral vestibulopathy (BVP). Forty-four people with BVP, 12 healthy young adults and 12 healthy older adults completed walking trials at 0.4m/s to 1.6m/s in 0.2m/s intervals on a dual belt, instrumented treadmill. Using a motion capture system and kinematic data, the means and coefficients of variation for step length, time, width and double support time were calculated. The BVP group also completed a video head impulse test and examinations of ocular and cervical vestibular evoked myogenic potentials and dynamic visual acuity. Walking speed significantly affected all assessed gait parameters. Step length variability at slower speeds and step width variability at faster speeds were the most distinguishing parameters between the healthy participants and people with BVP, and within people with BVP with different locomotor capacities. We observed for step width variability, specifically, an apparent persistent importance of vestibular function at increasing speeds. Gait variability was not associated with the clinical vestibular tests. Our results indicate that gait variability at multiple walking speeds has potential as an assessment tool for vestibular interventions. New & Noteworthy Walking speed significantly but differentially affects gait variability in healthy adults and in adults with bilateral vestibulopathy. Gait variability at different speeds distinguishes between participants with and without bilateral vestibulopathy, but also between more and less able walkers with bilateral vestibulopathy. Specifically, for step width variability, an apparent persistent importance of vestibular function at increasing walking speeds was observed. Gait variability was generally not correlated with clinical tests of vestibular function.
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Patients with bilateral vestibulopathy (BVP) suffer from persistent imbalance during standing and walking as well as an impaired gaze stabilization during head movements. Disabilities associated with BVP severely compromise patients' daily activities and are often linked to an increased risk of falls. Currently, the only established treatment option in BVP is physical therapy. However, treatment effects of physical therapy in BVP are most often limited and many patients do not adequately recover performance. Therefore, a number of technical therapeutic approaches are being explored that either try to substitute lost vestibular sensation with a congruent stimulation of other sense modalities or to artificially mimic vestibular function by means of an implantable vestibular prosthesis. Besides, attempts have recently been made to augment and optimize residual vestibular function in patients with BVP using an imperceptible noisy galvanic vestibular stimulation (nGVS). This approach is based on the natural phenomenon of stochastic resonance, wherein the signal processing in sensory systems can be improved by adding an appropriate level of noise to the system. Promising first study outcomes of nGVS treatment in patients with BVP indicate the feasibility of a future non-invasive sensory prosthetic device for BVP rehabilitation. This paper gives an overview about recent research on nGVS treatment in patients with BVP and discusses future research perspectives in this field.
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