Title: Automated ischemic beat classification using Genetic Algorithm based Principal Component Analysis
Authors: S. Murugan, S. Radhakrishnan
Addresses: Department of ICE, Arulmigu Kalasalingam College of Engineering, Srivilliputhur 626190, Tamil Nadu, India. ' Department of CSE, Arulmigu Kalasalingam College of Engineering, Srivilliputhur 626190, Tamil Nadu, India
Abstract: The ischemic beats from Electrocardiogram (ECG) signal detection are based on the specific part of the beat called the ST segment. The performance of the detection relies heavily on the relevant and efficient feature extraction of the ST segment. In this paper, the Genetic Algorithm (GA) is combined with PCA to extract more relevant features; the proposed method is named as Genetic based Principal Component Analysis (GPCA). The performance GPCA is compared with the linear PCA, and shown that the proposed GPCA extracts better features for ischemic classification.
Keywords: ischemia detection; ECG signals; PCA; principal component analysis; GAs; genetic algorithms; ischemic beat classification; electrocardiograms; neural networks; myocardial ischemia; heart disease.
International Journal of Healthcare Technology and Management, 2010 Vol.11 No.3, pp.151 - 162
Available online: 12 Jul 2010 *Full-text access for editors Access for subscribers Purchase this article Comment on this article