Detection of some heart diseases using fractal dimension and chaos theory

Abstract

This study evaluates the changes in heart rate variability for 13 signals ECG signals taken from the MIT-BIH arrhythmia database to detect some major heart disease (APC, PVC, RBB, LBB) with fractal dimension. Fractal dimension is one of the best known parts of fractal analysis. A huge number of dimensions have been defined in various fields. We choose the regularization dimension [1] for detection and prediction of some hearts failure. Nonlinear analysis based on chaos theory and fractal analysis techniques may quantify abnormalities. This article emphasizes changes in time series applied on patients with heart disease.