人体HRV信号的检测及其复杂性分析  

Measurement and Estimation of Complexity Analysis of Human HRV Signals

作　　者：韩清鹏[1] 

机构地区：[1]扬州大学环境科学与工程学院,江苏扬州225009

出　　处：《江南大学学报（自然科学版）》2007年第3期336-339,共4页Joural of Jiangnan University (Natural Science Edition)　

基　　金：国家自然科学基金项目(10402008)

摘　　要：设计开发了一种便携式心电监测仪器,用于监测人的肢体心电(ECG)信号.根据获得的心电数据,采用小波变换技术进行心电R峰的准确定位,进而得到HRV序列.对HRV信号进行复杂性分析的结果表明:处于健康状态下HRV信号的复杂度(C(N))要高于处于病理状态下HRV信号的复杂度,且近似熵和复杂度的分析结果一致;处于健康状态下HRV信号的近似熵要高于处于病理状态HRV信号的近似熵.A portable instrument for monitoring body electrocardiogram （ECG） is introduced in the paper. The R peaks of ECG signals are recognized based on wavelet transform technique from measured ECG, and the exact HRV data are constructed. Two algorithms were used as complexity measures to describe the complexity of nonlinear dynamic system. One was complexity C（N） and the other is approximate entropy（ApEn）. It was shown that when heart rate is normal the C（N） is higher than that of the Arrhythmia. The ApEn of the HRV has the same trend compared with the result of C（N）. It also implies that the arrhythmia is less chaotic than that of the normal.

关 键 词：心率变异 心电监测 复杂度 近似熵 

分 类 号：TP391.5[自动化与计算机技术—计算机应用技术] R318.04[自动化与计算机技术—计算机科学与技术]