使用先进AR模型表示的多功能表面肌电信号分类

Proceedings of 1994 20th Annual Northeast Bioengineering Conference Pub Date : 1994-03-17 DOI:10.1109/NEBC.1994.305164

R. Knox, D.H. Brooks

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引用次数: 17

摘要

已经讨论了自回归系数衍生的新特征在上肢肌电图模式识别中的潜在用途(Knox等人，15/sup / Ann)。Int。IEEE EMBS会议，圣地亚哥，加州，美国，1993年10月)。这些新特征(反射系数、倒谱系数和对数面积比)在语音处理中被大量使用。给出了一个非参数线性分类器的结果。

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Classification of multifunction surface EMG using advanced AR model representations

The potential use of new features derived from autoregressive coefficients for upper limb EMG pattern recognition has been discussed (Knox et al., 15/sup th/ Ann. Int. Conf. of the IEEE EMBS, San Diego, CA, USA, Oct. 1993). These new features (reflection coefficients, cepstral coefficients, and logarithmic area ratios) are used heavily in speech processing. Results from a nonparametric linear classifier are presented.<>

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Proceedings of 1994 20th Annual Northeast Bioengineering Conference

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