An approach to detect QRS complex using backpropagation neural network

Authors:
Mamun B. I. Reaz;Muhammad I. Ibrahimy;Rosminazuin A. Rahim
Affiliations:
Faculty of Engineering, Multimedia University, Cyberjaya, Malaysia;Kulliyyah of Engineering, International Islamic University, Selangor, Malaysia;Kulliyyah of Engineering, International Islamic University, Selangor, Malaysia
Venue:
NN'06 Proceedings of the 7th WSEAS International Conference on Neural Networks
Year:
2006

Citing 2
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Abstract

Backpropagation Neural Network is used to learn the characteristics of R peak to detect QRS complex. This allows R peak to be differentiated from large peaked T and P waves with higher accuracy and minimizes the problem associated with the noises in the ECG signal includes power line interference, motion artifacts, baseline drift, ECG amplitude modulation and other composite noises. The features that trains the network includes amplitude, differentiation value, duration exceed threshold, RR interval and crossing-zero. The performance was tested and resulting in accuracy to detect the correct positive peak was 91.16%.