In this study we intend to apply the advanced supervised learning methods, developed by Elad (14) in order to adaptively generate optimal dictionaries and representation methods for ECG signals and use these dictionaries to develop highly effective over complete dictionary based analysis methods in order to separate the complex ECG signal into its basic components and noise. We then intend to apply advanced statistical and data mining techniques in order to relate the basic patterns of the ECG signals to the pain sampled in the designed groups.