Identification of spring coefficient for heel rocker function support based on estimated dorsiflexion torque

Jing Chen Hong, Yuki Hayashi, Shigeru Suzuki, Yuta Fukushima, Kazuhiro Yasuda, Hiroki Ohashi, Hiroyasu Iwata

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

2 Citations (Scopus)

Abstract

In previous research, we have developed a high-dorsiflexion assistive robotic technology aiming for gait rehabilitation targeting on ankle dorsiflexion movement. A McKibben-type artificial muscle is applied to provide large dorsiflexion force while adding little weight to the device. This ensures the foot clearance before initial stance phase in gait. Meanwhile, a tension spring is deployed in series with the artificial muscle to support heel rocker function in loading response phase. Suitable spring coefficient for each individual differs according to ankle's dorsiflexion torque in loading response. An unsuitable spring would lead to knee deviation in this phase. In this study, we derived an identification equation to determine a suitable spring coefficient for individuals based on estimation of dorsiflexion torque required to support. An evaluation test on healthy objects was conducted, which shows no negative effects on participants' knee angles with the identified spring coefficient.

Original languageEnglish
Title of host publication2019 IEEE 16th International Conference on Rehabilitation Robotics, ICORR 2019
PublisherIEEE Computer Society
Pages355-359
Number of pages5
ISBN (Electronic)9781728127552
DOIs
Publication statusPublished - 2019 Jun
Event16th IEEE International Conference on Rehabilitation Robotics, ICORR 2019 - Toronto, Canada
Duration: 2019 Jun 242019 Jun 28

Publication series

NameIEEE International Conference on Rehabilitation Robotics
Volume2019-June
ISSN (Print)1945-7898
ISSN (Electronic)1945-7901

Conference

Conference16th IEEE International Conference on Rehabilitation Robotics, ICORR 2019
Country/TerritoryCanada
CityToronto
Period19/6/2419/6/28

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Rehabilitation
  • Electrical and Electronic Engineering

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