Adaptive Time Window Function Optimization Based Electrocardiography Feature Waveform Recognition

doi:10.13190/j.jbupt.2018-023

JOURNAL OF BEIJING UNIVERSITY OF POSTS AND TELECOM ›› 2019, Vol. 42 ›› Issue (4): 82-88.doi: 10.13190/j.jbupt.2018-023

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Adaptive Time Window Function Optimization Based Electrocardiography Feature Waveform Recognition

ZHANG Jin-ling, CUI Tong, LIU Wei-bin

School of Electronic Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, China

Received:2018-01-26 Online:2019-08-28 Published:2019-08-26

Abstract

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.

Key words: adaptive windowed wavelet transform, differential threshold, electrocardiography signal, feature waveform recognition

CLC Number:

TN929.53

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 TELECOM, 2019, 42(4): 82-88.

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Adaptive Time Window Function Optimization Based Electrocardiography Feature Waveform Recognition

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