A New Ventricular Late Potential Classification System Using Ant Colony Optimization

Abstract

Problem statement: Ventricular Late Potentials (VLPs) are low-level high frequency signals that are usually found within the terminal part of the QRS complex from patients after myocardial infarction. Patients with VLPs are at risk of developing ventricular tachycardia, which is the major cause of death if patients suffering from heart disease. Approach: Discrete Wavelet Transform was used to detect VLPs and then ANT Colony Optimization (ACO) was applied to classify subjects with and without VLPs. Results: A set of Discrete Wavelet Transform (DWT) coefficients was selected from the wavelet decomposition. Three standard parameters of VLPs such as QRST, D₄₀ and V₄₀ were established. After that a novel clustering algorithm based on Ant Colony Optimization was developed for classifying arrhythmia types. Conclusion: The wavelet decomposition enabled us to perform the task efficiently and produced reliable results.