NDLI: Use of galvanic vestibular feedback for a balance prosthesis

Content Provider	IEEE Xplore Digital Library
Author	Peterka, R.J.
Copyright Year	2012
Description	Author affiliation: Dept. of Biomed. Eng., Oregon Health & Sci. Univ., Portland, OR, USA (Peterka, R.J.)
Abstract	Activation of vestibular afferents by a bilateral bipolar galvanic vestibular stimulus (GVS) evokes medial-lateral (ML) body sway. By applying a GVS feedback signal that is a function of measured ML head motion, the potential exists for GVS to restore a useful vestibular contribution to ML balance control in vestibular-deficient subjects who remain responsive to GVS. A key to developing an effective balance prosthesis using GVS is to determine the functional relationship between GVS and its influence on the brain's internal estimate of head motion. We describe how a model-based interpretation of GVS-evoked body sway can be used to identify this functional relationship. Results indicate that the GVS-evoked internal motion estimate is effectively a low-pass filtered version of the GVS current. With preliminary data, we demonstrate that GVS feedback, compensated for the identified low-pass characteristics, can either remove the ability of a subject with normal vestibular function to use vestibular information for balance control, or can restore the ability of a subject with bilateral vestibular loss to maintain balance in a condition requiring vestibular information for balance control.
Sponsorship	IEEE Eng. Medicine Biol. Soc.
Starting Page	6137
Ending Page	6140
File Size	556086
Page Count	4
File Format	PDF
ISBN	9781424441198
ISSN	1557170X
e-ISBN	9781457717871
DOI	10.1109/EMBC.2012.6347394
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-08-28
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Prosthetics Information filters Electrodes Control systems Surface fitting Training
Content Type	Text
Resource Type	Article
Subject	Signal Processing Biomedical Engineering Health Informatics Computer Vision and Pattern Recognition

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