摘要
根据脉搏、心电信号与亚健康状态的内在联系,采用信息融合技术构建了基于脉搏功率谱峰值和脉搏波传输时间的特征向量,利用线性判别式对亚健康状态进行分类判别。50例样本的识别检验结果显示:亚健康状态对应的脉搏功率谱峰值显著降低[(42.3843±3.7116),(37.6022±4.4468),P<0.01],脉搏波传输时间显著减少[(326.5801±36.4035),(259.1023±67.3719),P<0.01],分类正确率可达90%。
In order to diagnose or evaluate sub-health state, we have used data fusion technology and developed a new method which is based on the hidden information among ECG and pulse signals. The characteristic was constructed with pulse power spectrum peak value and pulse transit time （PTT）. The classification of health state was realized by using linear discriminant analysis （LDA） method. The results showed that the pulse power spectrum peak value of sub-health state was decreased significantly when compared with health state[（42. 3843 ±3. 7116） vs. （37. 6022±4. 4468）, P〈0. 01], and the pulse transit time was also decreased significantly[（326. 5801±36. 4035） vs. （259. 1023±67. 3719）, P〈0. 013, The classification accurate rate can reach 90%.
出处
《生物医学工程学杂志》
EI
CAS
CSCD
北大核心
2009年第6期1181-1185,共5页
Journal of Biomedical Engineering
基金
国家自然科学基金资助项目(30670529)
甘肃省自然科学基金资助项目(3ZS061-A25-049)
关键词
亚健康
脉搏功率谱峰值
心电脉搏数据融合
脉搏波传输时间
线性判别式分析
Sub-health Peak value of pulse power spectrum Electrocardiogram and pulse data fusion Pulse transit time（PTT） Linear discriminant analysis （LDA）
