Forward estimation of joint torque from EMG signal through muscle synergy combinations

Zhan Li, Mitsuhiro Hayashibe, David Guiraud

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

2 Citations (Scopus)

Abstract

Human movement is a result of synergetic combinations of multiple muscle contractions. The summation of motor unit action potentials can be measured through Electromyography (EMG), thus the processed EMG can be regarded as the muscle activation to be employed to estimate joint movement or torque production. Such forward relationship for representing the joint torque can be established and identified through associated EMG/activations of extension and flexion muscle groups. On the other hand, muscle synergy always exists indicating how quantitatively central nervous system (CNS) drives correlated muscle groups to accomplish the joint torque generation. In this paper, we investigate the approaches of estimating the ankle joint torque from EMG/activatons of associated muscle groups. The approaches discussed fall into two main categories: i) full utilization of both of extension and flexion EMG/activations for estimating the joint torque; ii) exploitation of muscle synergy extraction of EMG/actvations and consequent usage of extracted components in reduced space for estimating the joint torque. Comparison is made between the two methods with experimental data of five able-bodied subjects. From the results we conclude that, method ii) with muscle synergy extraction may not degrade the performance of method i) but meanwhile show the the muscle synergic ratios for generating the joint torque, and involvement of joint position and velocity information can improve the estimation for both methods.

Original languageEnglish
Title of host publication2013 6th International IEEE EMBS Conference on Neural Engineering, NER 2013
Pages806-809
Number of pages4
DOIs
Publication statusPublished - 2013 Dec 1
Externally publishedYes
Event2013 6th International IEEE EMBS Conference on Neural Engineering, NER 2013 - San Diego, CA, United States
Duration: 2013 Nov 62013 Nov 8

Publication series

NameInternational IEEE/EMBS Conference on Neural Engineering, NER
ISSN (Print)1948-3546
ISSN (Electronic)1948-3554

Other

Other2013 6th International IEEE EMBS Conference on Neural Engineering, NER 2013
CountryUnited States
CitySan Diego, CA
Period13/11/613/11/8

ASJC Scopus subject areas

  • Artificial Intelligence
  • Mechanical Engineering

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