Title: Study of ECG signals based on gender and heart abnormalities

Authors: Anu Mehra; Monika Singhal; Rana Majumdar; Muskan Chotwani; Novita Sarkar; Shilpi Sharma

Addresses: Amity University Uttar Pradesh, Amity Road, Sector 125, Noida, Uttar Pradesh 201313, India ' Amity University Uttar Pradesh, Amity Road, Sector 125, Noida, Uttar Pradesh 201313, India ' Meghnad Saha Institute of Technology, Techno India Group, India ' Amity University Uttar Pradesh, Amity Road, Sector 125, Noida, Uttar Pradesh 201313, India ' Amity University Uttar Pradesh, Amity Road, Sector 125, Noida, Uttar Pradesh 201313, India ' Amity University Uttar Pradesh, Amity Road, Sector 125, Noida, Uttar Pradesh 201313, India

Abstract: Appropriate QRS detection of the ECG signal is extremely important for determining the variations in the heart rate. The two most famous algorithms for the QRS detection are Murthy and Rangaraj and Pan and Tompkin. Using these two algorithms, comparison of results for five different datasets i.e., MIT-BIH arrhythmia database, European ST-T database, the MIT-BIH Noise stress test database, the BIDMC congestive heart failure database and intracardiac atrial fibrillation database was done in MATLAB and comparative analysis was obtained on the basis of age, sex and heart rate (above 95 and below 60). Murthy and Rangaraj algorithm is the methodology which is derivative-based and provides results without any delay and gives reduced noise and sharp peak output. On the other hand, Pan and Tompkin algorithm performs the analysis of slope, width and amplitude of QRS complexes and is found to have higher accuracy than other real-time methods.

Keywords: database; ECG; heart rate; Murthy and Rangaraj; Pan and Tompkin.

DOI: 10.1504/IJCCIA.2020.105573

International Journal of Computational Complexity and Intelligent Algorithms, 2020 Vol.1 No.3, pp.277 - 291

Received: 28 May 2018
Accepted: 13 May 2019

Published online: 28 Feb 2020 *

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