【作者】 廖志伟； 李玉榕； 杜民；

【Author】 Liao Zhiwei1,2,,Li Yurong1,2,Du Min2(1.College of Electrical Engineering and Automation,Fuzhou University,Fuzhou,Fujian,350108,China;2.Fujian Key Laboratory of Medical Instrumentation & Pharmaceutical Technology,Fuzhou,Fujian,350002,China)

【机构】 福州大学电气工程与自动化学院； 福建省医疗器械和医药技术重点实验室；

【摘要】 本文基于sEMG噪声干扰主要有工频干扰和其他生理干扰的特点,采用独立成分分析的方法去除工频干扰,再对比采用小波消噪、小波包消噪、EMD阈值消噪等方法消除其余生理噪声。实验证明,ICA算法可以很好的分离50Hz工频噪声,EMD阈值消噪方法相对于其他方法也具有较高的信噪比,达到更好的消噪效果。更多还原

【Abstract】 This paper is based on the characteristic that sEMG noises main included power frequency interference and other physical interference.Independent Component Analysis is employed to remove power frequency interference,Wavelet denoising,Wavelet Packet denoising and EMD threshold denoising is employed to eliminate the remaining physiological noise.It is showed that ICA algorithm can be well used to separate 50Hz power frequency noise,EMD threshold denoising has high SNR compared with other methods,with a better denoising result.更多还原