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A Study on the Pattern Recognition of EMG Signals for Head Motion Recognition  

이태우 (서울시립대학교 전자전기 컴퓨터 공학부)
전창익 (서울시립대학교 전자전기 컴퓨터 공학부)
이영석 (청운대학교 전자공학과)
유세근 (청운대학교 전자공학과)
김성환 (서울시립대학교 전자전기 컴퓨터 공학부)
Publication Information
The Transactions of the Korean Institute of Electrical Engineers D / v.53, no.2, 2004 , pp. 103-110 More about this Journal
Abstract
This paper proposes a new method on the EMG AR(autoregressive) modeling in pattern recognition for various head motions. The proper electrode placement in applying AR or cepstral coefficients for EMG signature discrimination is investigated. EMG signals are measured for different 10 motions with two electrode arrangements simultaneously. Electrode pairs are located separately on dominant muscles(S-type arrangement), because the bandwidth of signals obtained from S-type placement is wider than that from C-type(closely in the region between muscles). From the result of EMG pattern recognition test, the proposed mIAR(modified integrated mean autoregressive model) technique improves the recognitions rate around 17-21％ compared with other the AR and cepstral methods.
Keywords
electromyography(EMG); pattern recognition; mIAR;
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Times Cited By KSCI : 1  (Citation Analysis)
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