Automated ischemic beat classification using Genetic Algorithm based Principal Component Analysis
by S. Murugan, S. Radhakrishnan
International Journal of Healthcare Technology and Management (IJHTM), Vol. 11, No. 3, 2010

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.

Online publication date: Mon, 12-Jul-2010

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