Control and Evaluation of Body Weight Support Walker for Overground Gait Training

Zonghao Dong, Jose Victorio Salazar Luces, Yasuhisa Hirata

Research output: Contribution to journalArticlepeer-review

Abstract

Gait rehabilitation training under robot-assisted partial Body Weight Support (BWS) is a promising technique that helps patients who suffer from a traumatic or congenital brain injury like stroke or cerebral palsy to become independent in daily life activities. In recent years, robotic BWS systems have been widely studied, where the BWS is provided by the robot while the user walks on devices fixed to the environment such as treadmills, thereby gaining functional benefits such as improved gait symmetry and increased walking speed. On the other hand, mobile BWS robots that allow conventional overground walking with well-designed control strategies have been less researched, limiting the widespread adoption of robotic rehabilitation because of the cost effectiveness of fixed robotic devices and poor portability. To address this problem, in our previous study, we developed a mobile BWS walker that allows for overground walking under variable levels of BWS. In this letter, we introduce a system architecture that integrates the walker with a pair of instrumented shoes and discuss different system control strategies including static and variable BWS control. When walking under Static-BWS (SBWS), the subject walks while a constant portion of his/her weight is supported, which might cause an unnatural gait. Using a Variable-BWS (VBWS), the provided BWS can be adjusted according to human's gait events to provide a more natural gait. This letter describes the system architecture, as well as experiments with able subjects that demonstrate the effectiveness of both the SBWS and VBWS control algorithms in relieving part of the subjects' body weight. Specifically, by synchronizing the controlled BWS with human gait events, users were able to walk more naturally, particularly under a high level of BWS.

Original languageEnglish
Article number9385949
Pages (from-to)4632-4639
Number of pages8
JournalIEEE Robotics and Automation Letters
Volume6
Issue number3
DOIs
Publication statusPublished - 2021 Jul

Keywords

  • physical human-robot interaction
  • Physically assistive devices

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Biomedical Engineering
  • Human-Computer Interaction
  • Mechanical Engineering
  • Computer Vision and Pattern Recognition
  • Computer Science Applications
  • Control and Optimization
  • Artificial Intelligence

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