Development of Walking Assist Robot with Body Weight Support Mechanism

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

4 Citations (Scopus)

Abstract

Gait rehabilitation is a necessary training process during early-stage treatment for patients suffering from stroke or Spinal Cord Injury (SCI). However, patients with decreased lower extremity muscle strength may have difficulty keeping the stability of the upper trunk and have the possibility of falling down. Therefore, it is necessary to provide patients with Partial Body Weight Support (PBWS) and to ensure safety during bipedal locomotion. In this paper, we introduce a mechatronic system design of a walking assist robot with Body Weight Support (BWS) mechanism to assist locomotor rehabilitation training for patients with stroke or SCI. The BWS functionality is realized by using a Variable Stiffness Mechanism (VSM) and ground load signals can be measured using a pair of force sensor-based robotic shoe systems. The proposed control system design is implemented in the QNX real-time operation system and the experimental result illustrates the validity of the proposed robotic architecture.

Original languageEnglish
Title of host publication2021 IEEE/SICE International Symposium on System Integration, SII 2021
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages554-559
Number of pages6
ISBN (Electronic)9781728176581
DOIs
Publication statusPublished - 2021 Jan 11
Event2021 IEEE/SICE International Symposium on System Integration, SII 2021 - Virtual, Iwaki, Fukushima, Japan
Duration: 2021 Jan 112021 Jan 14

Publication series

Name2021 IEEE/SICE International Symposium on System Integration, SII 2021

Conference

Conference2021 IEEE/SICE International Symposium on System Integration, SII 2021
Country/TerritoryJapan
CityVirtual, Iwaki, Fukushima
Period21/1/1121/1/14

Fingerprint

Dive into the research topics of 'Development of Walking Assist Robot with Body Weight Support Mechanism'. Together they form a unique fingerprint.

Cite this