To enhance the ECG classification performance, we should reduce the computational complexity which mainly occurs during the feature selection. Finding the right feature combinations is, indeed, a hard task. The computational requirements of exhaustive search methods (those which test all possible subsets) increase exponentially with the number of features in the original set.Thus we introduce sequential forward selection for the selection of feature subset. Sequential forward selection is attractive for feature selection in that the searching is based on simplest greedy search