摘要
提出以时域特征和模态能量商特征相结合进行脉象信号识别的方法。首先根据脉象信号的波形特征,计算脉象信号的h1,h3,h4,h3/h1,h4/h1,t1,t,k时域特征参数;然后对脉象信号进行EMD分解,计算6种脉象信号的模态能量商。通过临床200例脉象信号的采集和分析计算,获得临床上常见脉象信号的典型时域特征,确定弦脉的模态能量商R>1,滑脉、沉脉、细脉、缓脉、平脉的R值依次降低,且R<1。实验结果表明:时域特征和模态能量商特征相结合的方法可实现临床常见脉象信号的识别。
In this paper,a method is proposed in order to achieve the recognition of clinical pulse signals,that is,the combination of time domain characteristics and modal energy quotient characteristics. First,the time domain characteristic parameters h1,h3,h4,h3/h1,h4/h1,t1,t,k of pulse signals are calculated according to the pulse signal waveform characteristics. Second,based on EMD which can adaptively decompose the non—stationary signal,the pulse signals are decomposed to calculate the modal energy quotient. By analyzing and calculating 200 clinical cases of pulse signal,we acquired the typical time features of clinical common pulse signal,and determined wiry pulse modal energy quotient R1,slippery pulse,sunken pulse,fine pulse,slow pulse and flat veins R values in descending order,and R1. The results testify that the combination of time domain characteristics and modal energy quotient characteristics can effectively identify clinical common pulse signals.
出处
《长春理工大学学报（自然科学版）》
2015年第5期154-157,162,共5页
Journal of Changchun University of Science and Technology(Natural Science Edition)
基金
吉林省科技厅项目资助(20121016)
关键词
脉象信号
时域特征
EMD分解
模态能量商
pulse signal
time domain characteristics
EMD decomposition
modal energy quotient
