Robust sEMG electrodes configuration for pattern recognition based prosthesis control

Yinfeng Fang, Honghai Liu

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

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Electromyographic (EMG) signal is the electrical manifestation of a muscle contraction. Surface EMG signal can be obtained by electrodes on the skin to control prosthetic hand. However, surface EMG is sensitive to environmental interference, which leads to a low motion recognition rate of prosthesis control when encountering unexpected interferences, like electrodes shift. Electrodes shift occurs particularly in the day-to-day use of wearing electrodes. As a result, a long-term training procedure is necessary. To solve this problem, this paper proposes a new sEMG electrodes configuration to reduce the interference caused by electrodes shift. Experiments are designed to verify the improvements through evaluating the classification accuracy of discriminating eleven hand motions by pattern recognition approach. The comparison results show that the proposed electrodes configuration increases the pattern recognition rate by 4% and 8% when applied kNN and LDA classifier, respectively. This paper suggests that optimising electrodes configuration is able to improve the EMG pattern discrimination and the proposed electrodes configuration has reference value.
Original languageEnglish
Title of host publicationProceedings of the 2014 IEEE International Conference on Systems, Man and Cybernetics (SMC)
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)978-1-4799-3840-7
Publication statusPublished - Oct 2014
EventInternational Conference on Systems, Man and Cybernetics - San Diego, United States
Duration: 5 Oct 20148 Oct 2014

Publication series

ISSN (Print)1062-922X


ConferenceInternational Conference on Systems, Man and Cybernetics
Abbreviated titleSMC 2014
Country/TerritoryUnited States
CitySan Diego


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