R-Peak Identification in ECG Signals using Pattern-Adapted Wavelet Technique

Abstract

The electrocardiogram (ECG) signal consists of vital information that can be used in detecting various heart diseases. R-peaks in ECG signal play a major role in the diagnosis of the heart disorder. While numerous methods exist for the purpose, this research work aims at improving the efficiency of R-peak detection through a novel pattern-adapted wavelet designed to reduce the rate of false positives and the detection error. The experimental results show that the proposed pattern-adapted wavelet method achieves better performance when compared with the Symlet4 and other published methods. The new wavelet was designed using the least square optimisation method such that it not only approximates the given R-peak pattern of the ECG signal but also is admissible according to the constraints prescribed by Continuous Wavelet Transform (CWT). The algorithm uses the wavelet-specific property that CWT coefficients of a given signal are computed where local maximum and minimum pair appear around the signal peak location. When applied to the signals available through the standard MIT-BIH (Massachusetts Institute of Technology, Beth Israel Hospital) Arrhythmia database, Symlet4 detects R-peaks with an average of 98.73% accuracy, 99.99% sensitivity, 98.74% positive predictive value, 1.3336% error rate and overall F-score of 0.9937, while the proposed pattern-adapted wavelet detects the same with an average of 99.83% accuracy, 99.91% sensitivity, 99.92% positive predictive value, 0.16% error rate and overall F-score of 0.999.

KEYWORDS:

• Continuous Wavelet Transform (CWT)
• Denoising
• Electrocardiogram (ECG)
• MIT-BIH database
• Pattern-adapted wavelet
• R-peak
• RR-interval

Additional information

Notes on contributors

L. V. Rajani Kumari

L V Rajani Kumari, assistant professor, ECE, VNRVJIET, Hyderabad has completed BTech in ECE, MTech in Embedded Systems, and PhD degree. She has presented 20 research papers in International conferences/journals, in biomedical signal processing from JNTUH.

Y. Padma Sai

Y Padma Sai, professor and dean-student progression ECE, VNRVJIET, Hyderabad has received PhD in bio-medical signal processing from Osmania University. She is a senior member of IEEE, Life member of ISTE, ISOI, ASCI, and Fellow of IETE, IEI, Chairman for WIE Affinity Group IEEE Hyderabad Section. She has presented and published 80 research papers in national and international conferences/journals. One of the inventors of the patent published by Indian Patent office Titled, “A Method and System for Analysing Risk Associated with Respiratory Sounds.” She has received 2 awards (one Gold and special prize) from Korea International Women Invention Exposition (KIWIE-2019) as women entrepreneur of SALCIT Tech Nologies Private Limited. Email: [email protected]

N. Balaji

N Balaji, professor, ECE, and director, IQAC JNTUK, Kakinada has masters and PhD from Osmania University, Hyderabad. He has authored more than 50 research papers in national and international conferences and journals. He published 3 Patents in “The Patent Office Journal” and is still waiting for their Examination. Email: [email protected]