Cardiac arrhythmia diagnosis method using linear discriminant analysis on ECG signals

Yun Chi Yeh, Wen June Wang, Che Wun Chiou

研究成果: 雜誌貢獻期刊論文同行評審

134 引文 斯高帕斯(Scopus)

摘要

This work describes a Linear Discriminant Analysis (LDA) method to analyze ECG signals for diagnosing cardiac arrhythmias effectively. The proposed method can accurately classify and differentiate normal (NORM) and abnormal heartbeats. Abnormal heartbeats include left bundle branch block (LBBB), right bundle branch block (RBBB), ventricular premature contractions (VPC) and atrial premature contractions (APC). ECG signal analysis comprises three main stages: (i) QRS waveform detection; (ii) qualitative features selection; and (iii) heartbeat case determination. The available ECG records in the MIT-BIH arrhythmia database are utilized to illustrate the effectiveness of the proposed method. Experimental results show that the correct diagnosis rates are 98.97%, 91.07%, 95.09%, 92.63% and 84.68% for NORM, LBBB, RBBB, VPC and APC, respectively.

原文???core.languages.en_GB???
頁(從 - 到)778-789
頁數12
期刊Measurement: Journal of the International Measurement Confederation
42
發行號5
DOIs
出版狀態已出版 - 6月 2009

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