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基于自适应时间窗函数优化的心电特征波形识别
引用本文:张金玲,崔彤,刘为斌.基于自适应时间窗函数优化的心电特征波形识别[J].北京邮电大学学报,2019,42(4):82-88.
作者姓名:张金玲  崔彤  刘为斌
作者单位:北京邮电大学 电子工程学院,北京,100876;北京邮电大学 电子工程学院,北京,100876;北京邮电大学 电子工程学院,北京,100876
基金项目:国家自然科学基金项目(61771063)
摘    要:提出了自适应加窗小波变换方法,实现了心电特征波形精准定位.依据Q波和S波变化趋势识别出心电波有效起始点和终止点;结合差分阈值法检测QRS起始点,实现了心电特征波段的信息识别.研究结果表明,采用提出的定位识别方法,能对异常和亚健康心电波形进行有效识别,提高对QRS波群、特征P波和T波的识别度,对心电信息的提取和异常性心绞痛、心肌缺血、不稳定型心绞痛等心电异常诊断具有重要意义.

关 键 词:自适应加窗小波变换  差分阈值  心电信号  特征波形识别
收稿时间:2018-01-26

Adaptive Time Window Function Optimization Based Electrocardiography Feature Waveform Recognition
ZHANG Jin-ling,CUI Tong,LIU Wei-bin.Adaptive Time Window Function Optimization Based Electrocardiography Feature Waveform Recognition[J].Journal of Beijing University of Posts and Telecommunications,2019,42(4):82-88.
Authors:ZHANG Jin-ling  CUI Tong  LIU Wei-bin
Affiliation:School of Electronic Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, China
Abstract:An adaptive windowed wavelet transform method was proposed to make precision positioning of the electrocardiography feature waveforms. The effective starting and ending points of electrocardiography wave were identified according to the trend of Q wave and S wave. The information recognition of the electrocardiography characteristic band was realized by combining the differential threshold method to detect the QRS starting. It is shown that the proposed method can effectively identify abnormal and sub-healthy electrocardiography waveforms and improve the recognition of QRS wave group, P wave and T wave for extration of electrocardiography information and diagnosis of abnormal electrocardiography such as abnomal angina pectoris, myocardial ischemia and unstable angina pectoris.
Keywords:adaptive windowed wavelet transform  differential threshold  electrocardiography signal  feature waveform recognition  
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