A hybrid multi-channel surface EMG decomposition approach by combining CKC and FCM

Yong Ning, Shanan Zhu, Xiangjun Zhu, Yingchun Zhang

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

1 Scopus citations

Abstract

A hybrid approach is successfully developed in this study by combining the fuzzy C means (FCM) clustering method and Convolution Kernel Compensation (CKC) method for multi-channel surface electromyogram (EMG) decomposition. The FCM is utilized to estimate the initial innervation pulse trains (IPTs) of motor units (MUs) from a few channel surface EMG signals, the CKC method is then employed to estimate the final IPTs. Computer simulation results demonstrate the improved efficiency and accuracy of the hybrid approach compared to the classic CKC method.

Original languageEnglish (US)
Title of host publication2013 6th International IEEE EMBS Conference on Neural Engineering, NER 2013
Pages335-338
Number of pages4
DOIs
StatePublished - 2013
Event2013 6th International IEEE EMBS Conference on Neural Engineering, NER 2013 - San Diego, CA, United States
Duration: Nov 6 2013Nov 8 2013

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
Period11/6/1311/8/13

ASJC Scopus subject areas

  • Artificial Intelligence
  • Mechanical Engineering

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