Literature DB >> 32991291

A Home-Based Bilateral Rehabilitation System With sEMG-based Real-Time Variable Stiffness.

Yi Liu, Shuxiang Guo, Ziyi Yang, Hideyuki Hirata, Takashi Tamiya.   

Abstract

Bilateral rehabilitation allows patients with hemiparesis to exploit the cooperative capabilities of both arms to promote the recovery process. Although various approaches have been proposed to facilitate synchronized robot-assisted bilateral movements, few studies have focused on addressing the varying joint stiffness resulting from dynamic motions. This paper presents a novel bilateral rehabilitation system that implements a surface electromyography (sEMG)-based stiffness control to achieve real-time stiffness adjustment based on the user's dynamic motion. An sEMG-driven musculoskeletal model that incorporates the muscle activation and muscular contraction dynamics is developed to provide reference signals for the robot's real-time stiffness control. Preliminary experiments were conducted to evaluate the system performance in tracking accuracy and comfortability, which showed the proposed rehabilitation system with sEMG-based real-time stiffness variation achieved fast adaption to the patient's dynamic movement as well as improving the comfort in robot-assisted bilateral training.

Entities:  

Year:  2021        PMID: 32991291     DOI: 10.1109/JBHI.2020.3027303

Source DB:  PubMed          Journal:  IEEE J Biomed Health Inform        ISSN: 2168-2194            Impact factor:   5.772


  1 in total

1.  sEMG-Based Motion Recognition of Upper Limb Rehabilitation Using the Improved Yolo-v4 Algorithm.

Authors:  Dongdong Bu; Shuxiang Guo; He Li
Journal:  Life (Basel)       Date:  2022-01-03
  1 in total

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