计算机应用与软件2013，Vol.30Issue(3)：200-202,206,4.DOI:10.3969/j.issn.1000-386x.2013.03.053
脉搏信号和主成分分析在亚健康状态识别中的应用
APPLICATION OF PULSE SIGNAL AND PRINCIPAL COMPONENT ANALYSIS IN SUB-HEALTH STATE RECOGNITION
摘要
Abstract
In order to evaluate sub-health state, a novel sub-health state recognition method based on pulse signal is presented. Firstly, the wavelet transform is used to de-noise the pulse signal. Secondly, the power spectrum, approximate entropy and wavelet entropy estimation are employed to extract the characteristic quantity, and then to make principal component analysis on it. Finally, an improved linear discriminant analysis (LDA) is applied to classify and recognise. The rate of the principal component recognition is up to 100%. This method is simple in calculation, good in stability, and has high recognition rate, it is feasible to certain extent for sub-health state evaluation.关键词
亚健康状态/脉搏信号小波变换/主成分分析/线性判别式分析Key words
Sub-health state/ Pulse signal wavelet transform/ Principal component analysis (PCA)/ Linear discriminant/ analysis (LDA)分类
信息技术与安全科学引用本文复制引用
任亚莉,张爱华,孔令杰..脉搏信号和主成分分析在亚健康状态识别中的应用[J].计算机应用与软件,2013,30(3):200-202,206,4.
