ECG Feature Extraction plays a significant role in diagnosing most of the cardiac diseases. In this paper, a comparison between three ECG feature extraction methods is presented. The methods are: Linear Principal Components Analysis (PCA), Discrete Cosine Transformation (DCT) and Kernel Principal Components Analysis (KPCA). A Multilayer Perceptron is used as classifier and beats for training and validation of the classifier are extracted from twelve            MIT – BIH Arrhythmia Database registers. The performance of the three classifiers is discussed and a simple execution time evaluation is performed.