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一种基于互相关和多模板匹配的快速危急心律失常心电图波形识别方法。

A fast critical arrhythmic ECG waveform identification method using cross-correlation and multiple template matching.

作者信息

Chin Fook Joo, Fang Qiang, Zhang Tao, Cosic Irena

机构信息

School of Electrical & Computer Engineering, RMIT University, Melbourne, Australia.

出版信息

Annu Int Conf IEEE Eng Med Biol Soc. 2010;2010:1922-5. doi: 10.1109/IEMBS.2010.5628088.

Abstract

Critical Arrhythmic ECG such as Ventricular Tachycardia (VT) and Ventricular Fibrillation (VF) are both distinguishable by its waveform characteristics. A VF waveform is often described as disorganized and has an irregular rhythm while a VT waveform exhibits abnormal signatures and presents a regular rhythm pattern. This paper presents a fast cross-correlation algorithm using multiple waveform templates for automatic detection of life threatening arrhythmias such as VT and VF from the Normal Sinus Rhythm (NSR) waveforms. A sliding-window template cross-correlation technique is applied to an ECG signal to generate an array of correlation coefficients. Then a correlation coefficient curve is used to detect high coefficient values for a type of template that will quantify the similarity between an examined ECG signal and a template. The method presented in this paper is able to detect all three different types of ECG signals from a total 21 testing signal set with a satisfied correct rate.

摘要

诸如室性心动过速(VT)和心室颤动(VF)等严重心律失常的心电图都可以通过其波形特征来区分。VF波形通常被描述为杂乱无章且节律不规则,而VT波形则呈现出异常特征并具有规则的节律模式。本文提出了一种使用多个波形模板的快速互相关算法,用于从正常窦性心律(NSR)波形中自动检测诸如VT和VF等危及生命的心律失常。一种滑动窗口模板互相关技术被应用于心电图信号以生成一系列相关系数。然后,相关系数曲线用于检测某类模板的高系数值,该模板将量化被检查的心电图信号与模板之间的相似度。本文提出的方法能够从总共21个测试信号集中检测出所有三种不同类型的心电图信号,正确率令人满意。

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