We know that physiological signals such as ECG consist of mixtures of variety of patterns and phenomena accruing at different patterns and time points. Traditional analysis methods are designed and optimized to handle signals that include a single class of patterns such as pure harmonics or piece-wise constant functions. However, such basic operations that use a single representation method usually yield mediocre results when applied to real complex biological signals as ECG and EEG especially in the case where the Signal to Noise Ratio (SNR) is very low. Recent trends in digital signal processing (DSP) use the novel idea of merging several different representation methods to create a so called over-complete dictionary, examples of this approach include the Matching Pursuit algorithm and the Basis Pursuit algorithm. We intend to develop and apply the novel signal processing tools to the ECG signals for the first time. We believe that such tools have the potential to provide much better insight of the signal basic components and their relation to pain.