基于自适应时间窗函数优化的心电特征波形识别

Adaptive Time Window Function Optimization Based Electrocardiography Feature Waveform Recognition

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.

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 subhealthy 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.