Feasibility of entrainment with ankle mechanical perturbation to treat locomotor deficit of neurologically impaired patients

Jooeun Ahn, Tara Patterson, Hyunglae Lee, Daniel Klenk, Albert Lo, Hermano Igo Krebs, Neville Hogan

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

10 Scopus citations

Abstract

Entraining human gait with periodic torque from a robot may provide a novel approach to robot-aided walking therapy that is competent to exploit the natural oscillating dynamics of human walking. To test the feasibility of this strategy we applied a periodic ankle torque to neurologically impaired patients (one with stroke and one with multiple sclerosis). As observed in normal human walking, both patients adapted their gait periods to synchronize with the perturbation by phase-locking the robotic torque at terminal stance phase. In addition, their gait cadence became significantly faster due to the training with clear after effects when the perturbation ceased. These results support a new strategy for walking therapy that exploits an embedded neural oscillator interacting with peripheral mechanics and the resulting natural dynamics of walking, which are essential but hitherto neglected elements of walking therapy.

Original languageEnglish (US)
Title of host publication33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2011
Pages7474-7477
Number of pages4
DOIs
StatePublished - 2011
Externally publishedYes
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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