Enhancing the robustness of EMG-PR based system against the combined influence of force variation and subject mobility

Mojisola G. Asogbon Samuel, Oluwarotimi Williams Samuel, Yanjuan Geng, Paul Oluwagbenga Idowu, Shixiong Chen, R. Naik Ganesh, Pang Feng, Guanglin Li

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

2 Citations (Scopus)

Abstract

Inevitable variation in muscle contraction force while performing a target limb movement has been reported to have substantial impact on the performance of electromyography pattern recognition (EMG-PR) based prostheses. The mobility of subject has also been shown to cause changes in the EMG signal patterns when eliciting identical limb movement in mobile scenarios, thus leading to degradation in the overall performance of EMG-PR based prostheses. While the effect of variation in muscle contraction force and subject mobility (VMCF-SM) have only been studied individually, their combined effect on the performance of EMG-PR motion classifier remains unknown. Firstly, we investigated the combined effect of VMCF-SM on the performance of EMG-PR motion classifier by recording EMG signals from five able-bodied subjects in two scenarios (sitting and walking), across low (20% MVC), moderate (50% MVC), and high (80% MVC) muscle contraction force levels. Secondly, we proposed a new time-domain feature set (invTDF) that is robust to VMCF-SM and compared its performance with that of three different widely applied feature extraction methods. The proposed invTDF led to significant reduction in classification error in the range of 6.74% ~ 13.52% with respect to the other feature sets. These preliminary results indicate that using the proposed invTDF may increase the robustness of EMG-based myoelectric control against the combined effect of VMCF-SM.

Original languageEnglish
Title of host publicationProceedings of 2018 3rd Asia-Pacific Conference on Intelligent Robot Systems, ACIRS 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages12-17
Number of pages6
ISBN (Electronic)9781538672266
DOIs
Publication statusPublished - 17 Sep 2018
Externally publishedYes
Event3rd Asia-Pacific Conference on Intelligent Robot Systems, ACIRS 2018 - Singapore, Singapore
Duration: 21 Jul 201823 Jul 2018

Publication series

NameProceedings of 2018 3rd Asia-Pacific Conference on Intelligent Robot Systems, ACIRS 2018

Conference

Conference3rd Asia-Pacific Conference on Intelligent Robot Systems, ACIRS 2018
CountrySingapore
CitySingapore
Period21/07/1823/07/18

Keywords

  • effect of subjects' mobility
  • EMG-pattern recognition
  • muscle contraction force
  • upper-limb prostheses control

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