北京生物医学工程

基于小波变换的脉搏波信号高频噪声与呼吸基线的同时消除

Synchronous removal of high-frequency noise and breathing baseline in pulse wave signals based on wavelet analysis

作者：韩庆阳李丙玉王晓东

单位：                      中国科学院长春光学精密机械与物理研究所(长春130033)        

关键词：脉搏波信号；高频噪声；呼吸基线；小波变换

分类号：

出版年·卷·期（页码）：2014·33·3（247-252）

摘要：

目的光电容积脉搏波可用于血氧饱和度等人体生理参数的无创检测。由于信号采集过程中存在随机噪
声等干扰及人体呼吸等生理活动，脉搏波信号中存在高频噪声和呼吸基线漂移，影响最终的人体生理参数测
量精度。小波变换的多分辨性可使信号中的有用信息和噪声呈现出不同的特征。因此，本文提出采用基于小
波变换的方法对脉搏波信号进行高频噪声和基线的消除。方法首先根据每层小波细节的能量分布和一个周
期与整个多个周期的脉搏波信号最大分解层数确定分别代表高频噪声和呼吸基线的小波细节，然后同时消除
了人体生理参数检测中脉搏波信号的高频噪声和呼吸基线。利用自行研制的光电容积脉搏波采集装置采集脉
搏波信号，应用本文的方法同时消除信号中高频噪声和呼吸基线，并采用信号的频谱和交直流比R进行结果
评价。结果经过小波变换的处理之后信号频谱高频段幅值明显降低，交直流信号比R的稳定性明显增强。结
论小波变换有效地同时消除了高频噪声和呼吸基线，将有利于血氧饱和度等人体生理参数无创检测精度的
提高。

Objective Based on photoplethysmography can be used to noninvasively the
physiological parameters of human such as oxygen saturation and so on.Because of the
disturbance of random noise and breathing of human body in the process of signal acquisition,
there is high-frequency noise and breathing baseline, which affects the final prediction
accuracy of the physiological parameters of human, the resolution of wavelet transform can
make the signal and noise shows different characteristics.Therefore wavelet analysis is
employed, and then this can remove high-frequency noise and breathing baseline from pulse wave
signal.Methods Based on the energy of wavelet details and the maximum decomposition of a
period signal and the entire signal, we first confirm the details which represent high-
frequency noise and breathing baseline.Then the high frequency noise and baseline of pulse
wave signals in the human physiological parameter detection are eliminated.A self-developed
measurement device is used to obtain the pulse wave signal and wavelet transform is adopted to
decrease high-frequency noise and breathing baseline at the same time.And AC-DC modulation
employs ratio to evaluate the effect.Results After the management of wavelet transform, the
amplitude of high frequency declines and the stability of AC-DC modulation ratio
enhances.Conclusions Wavelet transform can effectively and synchronously remove high-frequency
noise and breathing baseline from pulse wave signal, which is beneficial for the improvement
of the detection accuracy in the physiological parameters of human body.

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