Clancy E A, Hogan N
Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge 02139.
IEEE Trans Biomed Eng. 1994 Feb;41(2):159-67. doi: 10.1109/10.284927.
Previous investigators have experimentally demonstrated and/or analytically predicted that temporal whitening of the surface electromyograph (EMG) waveform prior to demodulation improves the EMG amplitude estimate [1]-[6]. However, no systematic study of the influence of various whitening filters upon amplitude estimate performance has been reported. This paper describes a phenomenological mathematical model of a single site of the surface EMG waveform and reports on experimental studies which examined the performance of several temporal whitening filters. Surface EMG waveforms were sampled during nonfatiguing, constant-force, isometric contractions of the biceps or triceps muscles, over the range of 10-75% maximum voluntary contraction. A signal-to-noise ratio (SNR) was computed from each amplitude estimate (deviations about the mean value of the estimate were considered as noise). A moving average root mean square estimator (245ms window) provided an average +/- standard deviation (A +/- SD) SNR of 10.7 +/- 3.3 for the individual recordings. Temporal whitening with one fourth-order whitening filter designed per site improved the A +/- SD SNR to 17.6 +/- 6.0.
先前的研究人员已经通过实验证明和/或通过分析预测,在解调之前对表面肌电图(EMG)波形进行时间白化可以改善EMG幅度估计[1]-[6]。然而,尚未有关于各种白化滤波器对幅度估计性能影响的系统研究报道。本文描述了表面EMG波形单个部位的唯象数学模型,并报告了检验几种时间白化滤波器性能的实验研究。在肱二头肌或肱三头肌进行非疲劳、恒力等长收缩过程中,在最大自主收缩的10%-75%范围内对表面EMG波形进行采样。从每个幅度估计中计算信噪比(SNR)(估计值围绕平均值的偏差被视为噪声)。对于单个记录,移动平均均方根估计器(245ms窗口)提供的平均±标准差(A±SD)SNR为10.7±3.3。使用每个部位设计的一个四阶白化滤波器进行时间白化,可将A±SD SNR提高到17.6±6.0。