J Med Syst - Automatic classification of heartbeats using wavelet neural network.

Tópicos

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Resumo

The electrocardiogram (ECG) signal is widely employed as one of the most important tools in clinical practice in order to assess the cardiac status of patients. The classification of the ECG into different pathologic disease categories is a complex pattern recognition task. In this paper, we propose a method for ECG heartbeat pattern recognition using wavelet neural network (WNN). To achieve this objective, an algorithm for QRS detection is first implemented, then a WNN Classifier is developed. The experimental results obtained by testing the proposed approach on ECG data from the MIT-BIH arrhythmia database demonstrate the efficiency of such an approach when compared with other methods existing in the literature.

Resumo Limpo

electrocardiogram ecg signal wide employ one import tool clinic practic order assess cardiac status patient classif ecg differ patholog diseas categori complex pattern recognit task paper propos method ecg heartbeat pattern recognit use wavelet neural network wnn achiev object algorithm qrs detect first implement wnn classifi develop experiment result obtain test propos approach ecg data mitbih arrhythmia databas demonstr effici approach compar method exist literatur

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