基于不同白噪声幅值的总体平均经验模态分解法分析中医脉象的研究

Research of the EEMD Method to Pulse Analysis of Traditional Chinese Medicine Based on Different Amplitudes of the Added White Noise

总体平均经验模态分解(EEMD)能有效地解决经验模态分解(EMD)的模态混叠现象。将EEMD和Hil-bert-黄变换用于中医脉象信号的分析,在目标信号中分别加入幅度为原始信号幅值标准差0.1和0.2的白噪声,研究基于不同白噪声幅值的EEMD算法分解平脉、滑脉、弦脉及弦滑脉脉象信号所得各模态平均频率及平均能量的差异。研究结果显示,白噪声幅值为原始信号幅值标准差的0.2时的分解结果更符合临床实际。

The ensemble empirical mode decomposition（EEMD） can be used to overcome the mode mixing problem of empirical mode decomposition（EMD） effectively.The EEMD method and Hilbert-Huang Transform（HHT） can be used to analyze pulse signals of Traditional Chinese Medicine（TCM）.The amplitudes of the added white noise were about 0.1 and 0.2 time standard deviation of the investigated signal respectively.The difference of average frequency and average energy of every mode between normal pulse,slippery pulse,wiry pulse and wiry-slippery pulse were demonstrated based on different amplitudes of the added white noise.The results showed that it is more in line with clinical practice when the amplitude of the added white noise is about 0.2 time standard deviation of the investigated signal.