A real-time ECG analysis system using the db2 wavelet mother achieved 99.18% sensitivity, 99.15% positive predictive value, and 99.94% specificity for detecting premature ventricular contractions.
A real-time PVC detection system using Redundant Discrete Wavelet Transform demonstrates high sensitivity and specificity on the MIT-BIH Arrhythmia Database.
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.
Júnior et al. (Thu,) conducted a other in Premature Ventricular Contraction. Real-time PVC detection system based on Redundant Discrete Wavelet Transform was evaluated on PVC detection performance (Sensitivity). A real-time ECG analysis system using the db2 wavelet mother achieved 99.18% sensitivity, 99.15% positive predictive value, and 99.94% specificity for detecting premature ventricular contractions.