On the choice of the wavelets for ECG data compression

This paper presents a technique used to choose optimal wavelets for electrocardiogram (ECG) signal data compression. At present, it is not clear which wavelet function is suitable for data compression of ECG signals. An important issue is that the performance of wavelet based algorithms may depend on the particular basis chosen for the signal compression. Various criteria are used to evaluate the fidelity of the reconstruction. The percent root difference (PRD) has been widely used in the literature as the principal error criterion. In this paper, three more criteria are used, namely, signal to noise ratio (SNR), distortion (D), and root mean square error (RMSE). We use a multiwavelet system that can simultaneously provide perfect reconstruction while preserving length (orthogonality), good performance at boundaries (via linear-phase symmetry), and high order of approximation (vanishing moments). Experimental results are shown for both multiwavelets and scalar wavelets