Study of ECG signals based on gender and heart abnormalities. (28th February 2020)

• Record Type: Journal Article
• Authors: Mehra, Anu; Singhal, Monika; Majumdar, Rana; Chotwani, Muskan; Sarkar, Novita; Sharma, Shilpi
• Is Part Of: International journal of computational complexity and intelligent algorithms. Volume 1:Number 3(2019)
• Page Start: 277
• Page End: 291
• Publication Date: 2020-02-28
• Subjects: database -- ECG -- heart rate -- Murthy and Rangaraj -- Pan and Tompkin; Computational complexity -- Periodicals; Heuristic algorithms -- Periodicals; Neural networks (Computer science) -- Periodicals; 006.3
• Languages: English
• ISSNs: 2048-4720

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.