머리 움직임 인식을 위한 근전도 신호의 패턴 인식 기법에 관한 연구 = A Study on the Pattern Recognition of EMG Signals for Head Motion Recognition

다국어 초록 (Multilingual 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 recognition rate around 17-21% compared with other the AR and cepstral methods.

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