PERSPECTIVE article
Front. Neurol.
Sec. Neurorehabilitation
Volume 16 - 2025 | doi: 10.3389/fneur.2025.1609123
This article is part of the Research TopicNew methods in neurorehabilitationView all 3 articles
Optimizing noisy galvanic vestibular stimulation (nGVS) for postural control: Methodological considerations when individualizing the signal for people with bilateral vestibulopathy
Provisionally accepted
- 1Auckland University of Technology, Auckland, New Zealand
- 2University of Otago, Dunedin, Otago, New Zealand
- 3The University of Auckland, Auckland, Auckland, New Zealand
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An established aspect of noisy galvanic vestibular stimulation (nGVS) is tuning the nGVS signal to optimize stability on an individual basis. However, conventional tuning methods are strongly influenced by historical approaches and fail to integrate contemporary research findings. We outline a process used to integrate current physiological and neuroscientific insights into a robust method for personalizing nGVS signals to improve stability. We argue that an optimization protocol for a neuromodulatory nGVS signal designed to facilitate postural control needs to include: 1. A task that is relevant to the population, and which can be modified to give an appropriate level of challenge at an individual level; 2. Elements that can be reliably measured and are responsive to changes in postural control; 3. Well controlled and defined signal parameters; 4. Potential to be translated into the clinical setting. Questioning conventional methods enabled us to develop an alternative nGVS optimization assessment to enhance postural control in people with bilateral vestibulopathy. Refining this optimization assessment represents a crucial step in developing individualized nGVS interventions. The fundamental principles applied to develop our method can be adapted to other neuromodulatory stimuli across different impairments and populations.
Keywords: Neuromodulation, galvanic vestibular stimulation, NGVs, vestibular, Posture, balance, stochastic resonance, optimization
Received: 10 Apr 2025; Accepted: 28 May 2025.
Copyright: © 2025 McLaren, Smith, Taylor and Taylor. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Ruth McLaren, Auckland University of Technology, Auckland, New Zealand
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