The effects of limb position and external load on offline myoelectric pattern recognition control

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

Abstract

Limb position and load are factors that negatively affect myoelectric pattern recognition. While these effects have been studied separately, it remains unclear how limb position affects pattern recognition when limb load changes, and vice versa. Understanding this relationship will aid the development of algorithms and training protocols that allow prosthesis users to reliably grab and manipulate objects in various limb positions. We evaluated the effects of limb position and external load on offline pattern recognition accuracy in fourteen intact limb subjects and five below-elbow amputee subjects. Three clinically viable training methods were used to determine if training protocols can mitigate the negative effects of limb position and load. We found that limb position and load effects are independent in intact limb subjects, but are dependent in amputee subjects based on how the controller is trained. Although the advanced training protocols did not eliminate the limb position and load effects in most cases, they were able to reduce the effects and improve performance without increasing training time.

Original languageEnglish (US)
Title of host publication2020 8th IEEE RAS/EMBS International Conference for Biomedical Robotics and Biomechatronics, BioRob 2020
PublisherIEEE Computer Society
Pages654-659
Number of pages6
ISBN (Electronic)9781728159072
DOIs
StatePublished - Nov 2020
Event8th IEEE RAS/EMBS International Conference for Biomedical Robotics and Biomechatronics, BioRob 2020 - New York City, United States
Duration: Nov 29 2020Dec 1 2020

Publication series

NameProceedings of the IEEE RAS and EMBS International Conference on Biomedical Robotics and Biomechatronics
Volume2020-November
ISSN (Print)2155-1774

Conference

Conference8th IEEE RAS/EMBS International Conference for Biomedical Robotics and Biomechatronics, BioRob 2020
CountryUnited States
CityNew York City
Period11/29/2012/1/20

Keywords

  • limb position
  • load
  • myoelectric control
  • pattern recognition
  • prosthesis

ASJC Scopus subject areas

  • Artificial Intelligence
  • Biomedical Engineering
  • Mechanical Engineering

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