Citation: Appiah-Kubi, K.O.; Laing,
E.; Imtiaz, M.H. A Study Protocol to
Evaluate the Effects of Vestibular
Training on the Postural Control of
Healthy Adults Using Virtual Reality.
Appl. Sci. 2022, 12, 11937. https://
doi.org/10.3390/app122311937
Academic Editor: Zhihan Lv
Received: 30 September 2022
Accepted: 3 November 2022
Published: 23 November 2022
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Study Protocol
A Study Protocol to Evaluate the Effects of Vestibular Training
on the Postural Control of Healthy Adults Using Virtual Reality
Kwadwo O. Appiah-Kubi
1,
* , Evan Laing
2
and Masudul H. Imtiaz
3
1
Department of Physical Therapy, Clarkson University, Potsdam, NY 13699, USA
2
Department of Mechanical & Aerospace Engineering, Clarkson University, Potsdam, NY 13699, USA
3
Department of Electrical and Computer Engineering, Clarkson University, Potsdam, NY 13699, USA
* Correspondence: kappiahk@clarkson.edu; Tel.: +1-347-284-9986
Featured Application: This study protocol will promote efficient sensory reweighting and the
integration of postural control, and will modify vestibular and motor responses. The training will
be used as a rehabilitation protocol for neurological populations who have sensory integration
issues, including those with mild traumatic brain injuries, strokes, and multiple sclerosis.
Abstract:
Postural instability is a common symptom of vestibular dysfunction due to an insult to the
vestibular system. Vestibular rehabilitation is effective in decreasing dizziness and visual symptoms,
and improving postural control through several mechanisms, including sensory reweighting. As
part of the sensory reweighting mechanisms, vestibular activation training with headshake activities
influences vestibular reflexes. However, combining challenging vestibular and postural tasks to
facilitate more effective rehabilitation outcomes is underutilized. Our research goal is to develop a
virtual reality vestibular rehabilitation method for vestibular-postural control in neurological popula-
tions with vestibular and/or sensorimotor control impairment. The NeuroCom
®
SMART Balance
Master (Natus Medical Inc., Pleasanton, CA, USA), which was used in a prior study, is expensive
and bulky. Hence, a novel study protocol is established in this paper with the detailed objectives and
pre-/post-intervention data analysis pipeline (ANOVA, t-test, post hoc analysis, etc.) involving mod-
ern off-the-shelf sensors and custom instrumentation (electromyography, electrooculography, video
head impulse testing, force plates, and virtual reality headsets). It is expected that the training will
significantly decrease vestibuloocular reflex gains and eye movement variability, as well as reweight
the somatosensory ratio, finetune postural muscle activation, and consequently improve postural
flexibility and produce a faster automatic postural response. The findings may have implications for
the future development of vestibular rehabilitation protocols.
Keywords:
headshake; weight shift training; vestibular rehabilitation; vestibuloocular reflex; sensory
reweighting; virtual reality
1. Introduction
Vestibular dysfunction with poor postural stability is most common among the el-
derly [
1
,
2
] and contributes to their increased risk of falls [
3
]. Healthy postural stability
results from accurate somatosensory, visual, and vestibular inputs and the capacity of the
central nervous system (CNS) to weigh these sensory inputs to produce optimal postural
balance [
3
]. When visual and/or somatosensory inputs are inadequate or unreliable, the
CNS relies more heavily on the vestibular system for balance [
4
]. Untreated, patients often
exhibit signs and symptoms such as vertigo and poor balance which can be treated with
vestibular rehabilitation [
5
–
7
]. The goal of vestibular rehabilitation is to reduce dizziness,
improve gaze stabilization, correct the overdependence of the postural system on visual
and somatosensory inputs, and improve balance, gait, and quality of life [6,8]. The under-
lying neural mechanisms to achieve these purposes in vestibular rehabilitation include
Appl. Sci. 2022, 12, 11937. https://doi.org/10.3390/app122311937 https://www.mdpi.com/journal/applsci
