期刊名称：International Journal of Applied Science - Research and Review
电子版ISSN：2394-9988
出版年度：2018
卷号：5
期号：2
DOI：10.21767/2394-9988.100072
语种：English
出版社：Insight Medical Publishing
摘要：In this work, arrhythmia detection and classification from ECG signals has been performed using a digital signal processor- TMS320C6713. Two of the predominant ECG arrhythmias- premature ventricular contraction (PVC) and atrial fibrillation (AF) have been addressed in this work. In order to distinguish the PVC and AF beats from normal ECG beats, algorithms based on the morphological characteristics of arrhythmias have been applied. The PVC and AF beats present in ECG signals have been classified using correlation-based algorithm, in which a PVC or AF beats are compared/correlated with a normal ECG beat. The correlation coefficient value for normal ECG beats for a particular ECG signal is above 0.9 (highly correlated) whereas for a PVC or AF beats its value is in the range of 0.09 to 0.3 (highly uncorrelated). Another algorithm, based on slope/amplitude, has been implemented for detecting the PVC beats from ECG signals. The slope/ amplitude-based algorithm detects the PVC beats with 98.94% accuracy as compared to 65.20% accuracy by correlation-based algorithm. Thus, slope/amplitude-based algorithm outperforms the correlation-based algorithm as two parameters -the slope of QRS complex and R wave amplitude- are considered for detecting the abnormal beats. This work presents a DSP processor-based system, ideal for use in real time applications, for detecting PVC and AF beats from ECG signals.
关键词：ECG; Abnormal beat; Classification; Correlation based algorithm; Slope-Amplitude algorithm
