首页> 外文期刊>Journal of Electronics, Communication and Instrumentation Engineering Research >ARRHYTHMIA DETECTION USING ECG FEATURE EXTRACTION AND WAVELET TRANSFORM
【24h】

ARRHYTHMIA DETECTION USING ECG FEATURE EXTRACTION AND WAVELET TRANSFORM

机译:心电图特征提取和小波变换检测心律失常

获取原文
获取原文并翻译 | 示例
       

摘要

Cardiac Arrhythmia is the most common cause of death. These abnormalities of heart may cause sudden cardiac arrest or cause damage of heart. The early detection of arrhythmia is very important for the cardiac patients. Electrocardiogram (ECG) feature extraction system has been developed and evaluated based on the multi-resolution wavelet transform. ECG feature extraction plays a significant role in diagnosing most of the cardiac disease. One cardiac cycle in an ECG signal consist of the P-QRS-T waves. This feature extraction scheme determines the amplitudes and interval in the ECG signal for subsequent analysis. The amplitude and interval of P-QRS-T segment determine the function of heart. The ECG signal will be de-noised by removing the corresponding wavelet coefficients at higher scales. Then, QRS complexes are detected and each complex is use to locate the peaks of the individual waves, R-R interval which are present in one cardiac cycle and evaluated the algorithm on MIT-BIH Database, the manually annotated database, for validation purpose.
机译:心律失常是最常见的死亡原因。心脏的这些异常可能会导致心脏骤停或心脏受损。心律失常的早期检测对于心脏病患者非常重要。基于多分辨率小波变换的心电图(ECG)特征提取系统已经开发和评估。心电图特征提取在诊断大多数心脏病中起着重要作用。 ECG信号中的一个心动周期由P-QRS-T波组成。此特征提取方案确定ECG信号的幅度和间隔,以用于后续分析。 P-QRS-T段的幅度和间隔决定了心脏的功能。通过以较高的比例去除相应的小波系数,可以对ECG信号进行降噪。然后,检测QRS复合波,并使用每个复合波定位出现在一个心动周期中的各个波的峰,R-R间隔,并在手动注释的数据库MIT-BIH数据库上评估算法,以进行验证。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号