sEMG feature extraction

所属分类:人工智能/神经网络/深度学习
开发工具:matlab
文件大小:10KB
下载次数:36
上传日期:2018-04-01 11:08:01
上 传 者Jamsily
说明:  提取肌电信号的时域特征,ZC,WAMP,WL,SSC,RMS。以及特征的融合。肌电信号主要是采取了脚踝关节的六个动作。在动作识别中,时域的特征最常用,而且计算复杂度低,包含的信息也充分。
(The time domain features of electromyographic signals were extracted, ZC, WAMP, WL, SSC, RMS. And the fusion of features. The electromyographic signal mainly involves six movements of the ankle joint. In motion recognition, time domain features are most commonly used, and the computational complexity is low, and the information contained is sufficient.)

文件列表:
sEMG feature extraction\RootMeanSquare.m (4827, 2013-04-09)
sEMG feature extraction\SlopeSignChange.m (5070, 2013-04-09)
sEMG feature extraction\TimeDomain.m (7976, 2018-03-29)
sEMG feature extraction\WaveLength.m (4921, 2013-04-09)
sEMG feature extraction\WL_ZC_SSC_FDA_one.m (15100, 2013-04-09)
sEMG feature extraction\ZeroCrossing.m (5846, 2013-04-09)
sEMG feature extraction (0, 2018-03-29)

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