• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.10
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• pp.2551-2561
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• 2014

Several algorithms have been developed to detect AFIB(Atrial Fibrillation) which either rely on the linear and frequency analysis. But they are more complex than time time domain algorithm and difficult to get the consistent rule of irregular RR interval rhythm. In this study, we propose algorithm for optimal value detection of irregular RR interval for AFIB classification based on linear analysis. For this purpose, we detected R wave, RR interval, from noise-free ECG signal through the preprocessing process and subtractive operation method. Also, we set scope for segment length and detected optimal value and then classified AFIB in realtime through liniar analysis such as absolute deviation and absolute difference. The performance of proposed algorithm for AFIB classification is evaluated by using MIT-BIH arrhythmia and AFIB database. The optimal value indicate ${\alpha}=0.75$, ${\beta}=1.4$, ${\gamma}=300ms$ in AFIB classification.