DocumentCode :
3565539
Title :
Effect of ECG episodes on parameters extraction for paroxysmal atrial fibrillation classification
Author :
Abdul-Kadir, Nurul A. ; Safri, Norlaili M. ; Othman, Mohd A.
Author_Institution :
Comput. Eng. Dept., Univ. Teknol. Malaysia, Skudai, Malaysia
fYear :
2014
Firstpage :
874
Lastpage :
877
Abstract :
Atrial fibrillation is a type of atria arrhythmia which can cause the formation of blood clot in the heart. The blood clot may enlarge or moving to the brain and cause stroke. Therefore, this study monitors the performance of ECG episodes for paroxysmal atrial fibrillation classification. Episode of 2 seconds to 8 seconds were used to observe the performance of electrocardiograph (ECG) signal processing of atrial fibrillation patient classification. Methods of features extraction were based on the concept of describing short-term behaviour of complex physical and biological system, namely second order system (SOS), and with modified algorithm (hybrid with fast-Fourier transform, FFT). Features extracted from the ECG signal of atrial fibrillation patient were defined using three parameters, i.e. natural frequency, forcing input and damping coefficient. A total of twelve parameters were observed. Comparisons of performance between length of ECG episodes were explored for SOS, FFT-SOS and SOS-FFT algorithms. The episode of 4 seconds using SOS algorithm provides the highest accuracy (98 %) during the classification of ECG signal.
Keywords :
damping; diseases; electrocardiography; fast Fourier transforms; feature extraction; medical signal processing; signal classification; ECG episode effect; ECG episode length; ECG episode monitoring; ECG signal classification accuracy; ECG signal processing performance; FFT hybrid; FFT-SOS algorithm; SOS-FFT algorithm; atrial arrhythmia; atrial fibrillation patient; blood clot enlargement; blood clot movement; brain; complex biological system short-term behaviour; complex physical system short-term behaviour; damping coefficient; electrocardiograph; fast-Fourier transform hybrid; features extraction; forcing input; heart blood clot formation; modified algorithm; natural frequency; parameter extraction; paroxysmal atrial fibrillation classification; second order system; stroke; time 2 s to 8 s; Accuracy; Atrial fibrillation; Classification algorithms; Electrocardiography; Feature extraction; Monitoring; Rhythm;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Biomedical Engineering and Sciences (IECBES), 2014 IEEE Conference on
Type :
conf
DOI :
10.1109/IECBES.2014.7047637
Filename :
7047637
Link To Document :
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