Introduction to statistical pattern recognition (2nd ed.)
Introduction to statistical pattern recognition (2nd ed.)
Pattern Classification (2nd Edition)
Pattern Classification (2nd Edition)
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In order to improve the classification results on electrocardiogram (ECG) signals, Optimal Discrimination Plane (ODP) approach is introduced. Features are extracted from time-series data using the ODP that is developed by Fisher’s criterion method. ECG patterns are projected onto two orthogonal vectors, and the two-dimensional feature vectors are used as features to represent the ECG segments. Two types of ECG signals are obtained from MIT-BIH database, namely normal sinus rhythm and premature ventricular contraction. A quadratic discriminant function based classifier and a threshold vector based classifier are employed to classify these ECG beats, respectively. The results show the proposed technique can achieve better classification results compared to that of some recently published on arrhythmia classification.