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Kora Padmavathi
Gokaraju Rangaraju Institute of Engineering and Technology
Computer Science & IT Electrical & Electronics Engineering

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Detection of Atrial Fibrillation using Autoregressive modeling Kora Padmavathi; K.Sri Ramakrishna
International Journal of Electrical and Computer Engineering (IJECE) Vol 5, No 1: February 2015
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (210.461 KB) | DOI: 10.11591/ijece.v5i1.pp64-70

Abstract

A‎atrial fibrillation (AF) is the arrhythmia that commonly causes death in the adults. We measured AR coefficients using Burg’s method for each 15 second segment of ECG. These features are classified using the different statistical classifiers: kernel SVM and KNN classifier. The performance of the algorithm was evaluated on signals from MIT Physionet database.. The effect of AR model order and data length was tested on the classification results. This method shows better results can be used for practical use in the clinics.‏
Co-Authors K.Sri Ramakrishna