Neural Network (NN) is designed to detect QRS complex from ECG signal. QRS complex detection is essential so that RR-interval can be measured for disease classification and can also be monitoring the heart rate. In this paper, a supervised Neural Network based algorithm has been used to detect R in QRS complex. It was tried to find out the R-peak in QRS complex with missing peak and false peak as well, so that the correct decision can be made by the physician and clinician. The accuracy of finding the R-peak by using the Neural Network was 99.09% averagely and the average percentage of missing and false peak was 00.09%. The technique appears to be exceedingly robust, correctly detects R-peaks even aberrant QRS complexes in noise-corrupted ECGs. © 2008 Springer-Verlag.
CITATION STYLE
Hasan, M. A., Ibrahimy, M. I., & Reaz, M. B. I. (2008). NN-based R-peak detection in QRS complex of ECG signal. In IFMBE Proceedings (Vol. 21 IFMBE, pp. 217–220). Springer Verlag. https://doi.org/10.1007/978-3-540-69139-6_57
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