基于改进小波变换的心脏骤停识别

Syed Hassaan Ahmed, N. Razzaq, T. Zaidi
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引用次数: 1

摘要

心电图(ECG)是用来测量和诊断心电活动的。从心电信号中检测R峰值是我们的主要目标。它是鉴别不同心律失常的基本标志。本文利用小波变换进行R波提取,用于心脏骤停的识别。心源性猝死是一个全球性的健康问题。分析显示,全世界有数百万人死于SCD。我们需要一种合适而准确的方法来鉴别它。采用改进的小波变换方法从心电信号中提取R峰,然后借助MATLAB软件从心电信号中提取RR区间进行SCA识别。这里进行了一个简短的比较,以确定SCA患者与正常患者。利用MIT BIH数据库对算法进行了评价。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Identification of Sudden Cardiac Arrest (SCA) using Modified Wavelet Transform
Electro Cardiogram (ECG) is used to measure and diagnose electrical activity of heart. R peak detection from ECG signal is our main goal. It is the basic mark for identification of different arrhythmias. In this paper, R wave extraction is performed by using Wavelet Transform for the identification of Sudden Cardiac Arrest (SCA). Sudden cardiac death (SCD) is a global health issue. Analysis revealed that millions of people all around the world die as the result of SCD. We need to purpose a suitable and accurate method for its identification. Modified Wavelet Transform method is used for the extraction of R peaks from ECG signal and then RR interval is extracted from ECG signal with the help of MATLAB software to identify SCA. Here a brief comparison is performed to identify SCA patient with Normal Patient. The MIT BIH database has been utilized for evaluating the algorithm.
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