窦性和房性心律失常的DFA分析

研究证据表明许多自然系统和生物系统没有固定的特征尺度,而是展现自相似特性。本文利用消除趋势波动分析(DFA)方法,分析窦性心律、房性心律失常的ECG信号的自相似特性,以实现这两种心律失常的检测。并利用DFA方法对MIT-BIH标准数据库中的正常窦性心律、房性期前收缩(也称为房性早搏)、窦性心动过缓信号进行了分析和检测,得到这三种信号的尺度指数,据此区分出窦性心律、房性心律失常和正常窦性心律,此结果表明DFA方法能够检测窦性和房性心律失常。

Detection of Sinus Arrhythmias and Atrial Arrhythmias Based on Detrended Fluctuation Analysis

Recently, more and more evidences suggest that many natural systems and biological systems have no fixed characteristic scales, but they exhibit self-similarity. This study applied the .detrended fluctuation analysis （DFA） method, analyzing sinus rhythm, atrial arrhythmia ECG signals in self-similarity in order to achieve the two kinds of arrhythmia detection. First we obtained the normal sinus rhythm（NSR） data from the MIT-BIH normal sinus database, obtained the atrial premature contraction （APC） and sinus bradycardia rhythm（SBR） data from the MIT-BIH arrhythmia database. Then we detected and analyzed the NSR, APC and SBR signals with DFA method and acquired the scaling exponentαof the three signals. Finally we achieved the distinction among these three signals. The results showed that the DFA method could be used for detecting the sinus and atrial arrhythmias.