摘要
针对表面肌电信号是非线性非稳态信号的特点,为了得到信号的有效特征并对信号特征进行有效分析,采用HHT(Hilbert-Huang Transformation)分析方法,通过经验模态分解将信号分解为一组内蕴模态函数。基于各内蕴模态函数的频率特征的分析,对它们进行HHT变换建立表面肌电信号的时间-频率-能量三维Hilbert谱,进而得到信号的边际谱。文中给出基于经验模态分解阈值消噪方法,和小波阈值方法相比,其消噪效果明显,在抑制噪声的同时,能够较好保留信号边缘和细节信息。初步实验表明HHT方法为表面肌电信号的特征提取和模式识别提供了可靠的依据,具有很好的应用前景。
Surface electromyography （SEMG） was a nonlinear and nonstationary signal. In order to get effective features of the SEMG and analyze features, HHT method was applied. The signal could be decomposed by using the empirical mode decomposition （EMD） method into a series of intrinsic mode function （IMF） components, at the same time, the frequency of each IMF was analyzed. these IMFs were transformed into 3-D Hilbert spectra which exhibited the time-frequency-amplitude, and then the marginal spectra were obtained by integrating the Hilbert spectra with respect to time. A wavelet threshold filtering method based on EMD was proposed, this method has good effect on suppressing noise, comparing with wavelet threshold filter and has advantages of retaining edge and detail information. Experimental results show that HHT method provides reliable basis for the feature extraction and pattern recognition of SEMG of the lower limb and has a good prospect of application.
出处
《传感技术学报》
CAS
CSCD
北大核心
2010年第3期297-302,共6页
Chinese Journal of Sensors and Actuators
基金
国家自然科学基金资助(60705010)
浙江省自然科学基金资助(Y1080854)
