The design of a rehabilitation training system with EMG feedback for stroke patients

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

Abstract

Rehabilitation training systems have been widely used to help patients recover muscle function in recent years. However, most of the systems are not so suitable for stroke patients. Combined with the neuromuscular function characteristics of stroke patients, this study introduces a rehabilitation training system with surface electromyography (sEMG) feedback based on the ARM embedded system and LabVIEW. This system could not only perform real-time multi-channel surface electromyography (sEMG) signal acquisition, processing and multi-monitor, but also compute muscle fatigue level of patients’ trained parts and other related parameters during the training process. The verification results showed that the whole system was stable and had good interactivity. More importantly, the open system provided a convenient method to update design according to clinical feedback.

Original languageEnglish
Title of host publicationBioinformatics and Biomedical Engineering - Proceedings of the 9th International Conference on Bioinformatics and Biomedical Engineering, ICBBE 2015
EditorsJames J. Chou, Huaibei Zhou
PublisherCRC Press/Balkema
Pages277-282
Number of pages6
ISBN (Print)9781138027848
DOIs
StatePublished - 2016
Event9th International Conference on Bioinformatics and Biomedical Engineering, ICBBE 2015 - Shanghai, China
Duration: 18 Sep 201520 Sep 2015

Publication series

NameBioinformatics and Biomedical Engineering - Proceedings of the 9th International Conference on Bioinformatics and Biomedical Engineering, ICBBE 2015

Conference

Conference9th International Conference on Bioinformatics and Biomedical Engineering, ICBBE 2015
Country/TerritoryChina
CityShanghai
Period18/09/1520/09/15

Keywords

  • Characteristic parameters
  • Embedded system
  • LabVIEW
  • Stroke
  • sEMG feedback

Fingerprint

Dive into the research topics of 'The design of a rehabilitation training system with EMG feedback for stroke patients'. Together they form a unique fingerprint.

Cite this