Real-time premature ventricular contractions detection based on Redundant Discrete Wavelet Transform

• Published in: Research on biomedical engineering Vol. 34; no. 3; pp. 187 - 197
• Main Authors: Arrais Junior, Ernano, Valentim, Ricardo Alexsandro de Medeiros, Brandão, Gláucio Bezerra
• Format: Journal Article
• Language: English
• Published: Sociedade Brasileira de Engenharia Biomédica 01.09.2018
• Subjects: ENGINEERING, BIOMEDICAL; Premature ventricular contraction; Electrocardiogram; Redundant Discrete Wavelet Transform
• ISSN: 2446-4732; 2446-4740; 2446-4740
• DOI: 10.1590/2446-4740.01618

Abstract Introduction Premature Ventricular Contraction (PVC) is among the most common types of ventricular cardiac arrhythmia. However, it only poses danger if the person suffers from a heart disease, such as heart failure. Hence, this is an important factor to consider in heart disease people. This paper presents an ECG real-time analysis system for PVC detection. Methods This system is based on threshold adaptive methods and Redundant Discrete Wavelet Transform (RDWT), with a real-time approach. This analysis is based on wavelet coefficients energy for PVC detection. It is presented also a study to find the most indicated wavelet mother for ECG analysis application among the following wavelet families: Daubechies, Coiflets and Symlets. The system detection performance was validated on the MIT-BIH Arrhythmia Database. Results The best results were verified with db2 wavelet mother: the Sensitivity Se = 99.18%, Positive Predictive Value P+ = 99.15% and Specificity Sp = 99.94%, on 80.872 annotated beats, and 61.2 s processing speed for a half-hour record. Conclusion The proposed system exhibits reliable PVC detection, with real-time approach, and a simple algorithmic structure that can be implemented in many platforms.