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表面肌电信号的降噪处理
引用本文:李佳妮,王云峰.表面肌电信号的降噪处理[J].传感器与微系统,2017,36(7).
作者姓名:李佳妮  王云峰
作者单位:中国科学院大学中国科学院微电子研究所新一代通信射频芯片技术北京市重点实验室,北京,100029
摘    要:表面肌电信号是一种易受多种噪声影响的生物电信号,其中以工频干扰、基线漂移、白噪声等干扰尤为严重.通过分析噪声干扰的特点,结合表面肌电信号特征,选取频谱插值法在频域内消除了工频干扰;利用形态学滤波的开闭运算得到基线漂移特征,从而滤除了基线漂移;基于经验模态分解(EMD)得到的本质模态函数分析消除了白噪声.实验结果表明:上述滤波方法在不损坏有用信号的前提下,可以实现较为满意的滤波效果.

关 键 词:表面肌电信号  频谱插值  形态学滤波  经验模态分解

Noise reduction processing of surface electromyography signal
LI Jia-ni,WANG Yun-feng.Noise reduction processing of surface electromyography signal[J].Transducer and Microsystem Technology,2017,36(7).
Authors:LI Jia-ni  WANG Yun-feng
Abstract:Surface electromyography(sEMG) signal is noise-sensitive biological signal,particularly susceptible to power frequency,baseline drift,white noise.Based on analysis on features of noise interference and combined with feature of sEMG signal,use spectrum interpolation method to eliminate working frequency interference in frequency domain.And utilize opening and closing operation of morphological filtering to acquire characteristics of baseline drift,so as to remove baseline drift from the signal.Based on analysis on intrinsic mode functions obtained by empirical mode decomposition (EMD),white noise can be eliminated.Experimental results show that the above filtering method can achieve satisfied filtering effect without damaging useful signal.
Keywords:surface electromyography(sEMG) signal  spectrum interpolation  morphological filtering  empirical mode decomposition(EMD)
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