Open AccessAnalysis of Pan-Tompkins Algorithm Performance with Noisy ECG Signals
Author(s) -
M. A. Z. Fariha,
Ryojun Ikeura,
Soichiro Hayakawa,
Shigeyoshi Tsutsumi
Publication year - 2020
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1532/1/012022
Subject(s) - qrs complex , computer science , noise (video) , reliability (semiconductor) , algorithm , signal (programming language) , artificial intelligence , pattern recognition (psychology) , quality (philosophy) , speech recognition , medicine , power (physics) , philosophy , physics , epistemology , quantum mechanics , cardiology , image (mathematics) , programming language
The Pan-Tompkins Algorithm is the most widely used QRS complex detector for the monitoring of many cardiac diseases including in arrhythmia detection. This method could provide good detection performance with high-quality clinical ECG signal data. However, the numerous types of noise and artefacts that exist in an ECG signal will produce low-quality ECG signal data. Because of this, the performance of Pan-Tompkins-based QRS detection methods using low-quality ECG signals should be further investigated. In this paper, the performance of the Pan-Tompkins algorithm was analysed in extracting the QRS complex from standard ECG data that includes noise-stressed ECG signals. The algorithm’s QRS detection reliability was tested using MIT-BIH Noise Stress Test data and MIT-BIH Arrhythmia data. The performance of the algorithm was then analysed and presented. This paper shows the capability of the Pan-Tompkins algorithms in handling noisy ECG signals.