A balance control model predicts how vestibular loss subjects benefit from a vibrotactile balance prosthesis

Adam D. Goodworth, Conrad Wall, Robert J. Peterka

Research output: Chapter in Book/Report/Conference proceedingConference contribution

11 Scopus citations

Abstract

A balance control model was applied to interpret how subjects with a severe vestibular loss (VL) used vibrotactile information from a balance prosthesis to enhance balance control. Experimental data were from 5 VL subjects standing with eyes closed and responding to continuous pseudorandom surface tilts of the stance platform. Results showed that vibrotactile feedback information reduced sway at frequencies below 0.6 Hz, but vibrotactile feedback was less effective in reducing sway as stimulus amplitude increased. This experimental pattern was accurately predicted by the model, which was based on time-delayed sensory feedback control. The model predicted that changes to the vibrotactor activation scheme could improve performance of the prosthesis and demonstrated that further improvements might be possible if motor learning, acquired by practice and training, could increase VL subjects' reliance on the prosthesis.

Original languageEnglish (US)
Title of host publication33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2011
Pages1306-1309
Number of pages4
DOIs
StatePublished - 2011
Event33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2011 - Boston, MA, United States
Duration: Aug 30 2011Sep 3 2011

Publication series

NameProceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
ISSN (Print)1557-170X

Other

Other33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2011
Country/TerritoryUnited States
CityBoston, MA
Period8/30/119/3/11

ASJC Scopus subject areas

  • Signal Processing
  • Biomedical Engineering
  • Computer Vision and Pattern Recognition
  • Health Informatics

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