Abstract
Electrocardiography (ECG or EKG) is a medical test that is heavily used to assess human heart condition and investigate a large set of cardiac diseases. Automated ECG analysis has become a task of increased clinical importance since it can aid physicians in improved diagnosis. Most of the automated ECG analysis techniques require first identifying the onset and offset locations of its fiducial points and characteristic waves. Two of the important characteristic waves are P and T waves. They mark the beginning and end of an ECG cycle, respectively. In this paper, a fast technique is proposed that can segment ECG signals by accurately identifying the P and T waves. In this work, we evaluate the performance of our model on standard QT database (Laguna et al. Comput Cardiol 24:673–676, 1997 [1]). We achieved high accuracies above 99% and 97% while detecting P waves and T waves respectively.
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Bisharad, D., Dey, D., Bhowmick, B. (2020). A Fast Method for Segmenting ECG Waveforms. In: Elçi, A., Sa, P., Modi, C., Olague, G., Sahoo, M., Bakshi, S. (eds) Smart Computing Paradigms: New Progresses and Challenges. Advances in Intelligent Systems and Computing, vol 766. Springer, Singapore. https://doi.org/10.1007/978-981-13-9683-0_22
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DOI: https://doi.org/10.1007/978-981-13-9683-0_22
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