基于脉象信号的亚健康状态的识别

Recognition of sub-health status by using pulse signal

提出了一种新的识别亚健康状态的方法.利用HK-2000C集成化数字脉搏传感器提取人体左关处桡动脉脉搏信号,然后计算脉搏功率谱,并在此基础上提取功率谱峰值及功率谱重心,并将它们对应的频率作为特征量,利用线性判别式分析(LDA)对所提特征进行分类.经对30例样本的识别检验,结果表明,用功率谱重心及重心频率作为特征量分类率达到80%,用功率谱峰值和峰值频率作为特征量,分类正确率达到了86.667%.

A new method for identifying the sub-health status was presented. Pulse signal of radial artery were picked up by using HK-2000C digital integrated pulse transducer, and then the power spectrum of the pulse was calculated. Then the peak value, peak frequency, center of gravity （cg） and gravity frequency of power spectrum were extracted. And a linear discriminant analysis （LDA） was used to classify them for pattern recognition of sub-health. It was shown by checking the recognition of 30 sampling cases that the recognition accuracy of 80 % was attained by using cg and gravity frequency of power spectrum as the characteristics. And the recognition accuracy was 86. 667% by using peak value and peak frequency of power spectrum as characteristics.