摘要
为了更好地消除混杂在脑电信号中的噪声,完成脑电分析,对小波和希尔伯特变换(HHT)的脑电信号消噪效果进行了对比研究。在HHT消噪方法中,利用经验模态分解(EMD)算法对脑电信号进行8尺度分解,得到固有模态函数(IMF)分量的组合,经过滤波和信号重构,得到消噪后的脑电信号。实验结果表明,HHT方法能较好地去除脑电信号中的噪声。运用评价准则比较了HHT方法和小波变换方法的消噪效果,发现HHT方法的脑电信号消噪效果优于传统的小波变换消噪,且算法的效率更高。
To eliminate the noises mixed in the EEG effectively for completing the EEG analysis, a comparative research is made about the EEG de-noising effects of wavelet and Hilbert transform. In the HHT de-noising method, using empirical mode decomposition algorithm to have 8 scales of decomposition for the EEG, and get the combination of components of intrinsic mode functions, then reconstruct the filtered signal, obtain the EEG ~ter de-noising finally. Experimental results show that HHT method can properly remove the noises which contained in the EEG. The de- noising effects of HHT method and the wavelet transform method are compared by using the evaluation indexes. It finds that HI:IT method is better than the traditional wavelet transform in the EEG de-nosing and the efficiency of the HHT method is higher.
出处
《计量学报》
CSCD
北大核心
2013年第6期567-572,共6页
Acta Metrologica Sinica
基金
国家自然科学基金(61172134
61201300)
浙江省自然科学基金(LYl2F03006)