This work shows an effective application of Artificial Neural Network using the modified approach to support supervised learning, and the evaluation of its performance in the classification of R-R Interval of the Electrocardiogram (ECG) from patients with cardiac arrhythmias. A second aim of this study is to investigate the ability of ANN to classify R-R Interval when the original data samples are used as input variables. The classifier is developed and tested with the MIT-BIH Arrhythmia Database. The obtained results become equivalent to the most sophisticated methods in the literature when input data are properly pre-processed and the final classifier is allowed to adapt to the normal pattern of each analyzed patient.

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ECG Artificial Neural Network Back propagation algorithm Training Learning parameter RBF