Optimal discrete wavelet design for cardiac signal processing

The question of designing the best wavelet for a given signal is discussed from the perspective of orthogonal filter banks. Two performance criteria are proposed to measure the quality of a wavelet, based on the principle of maximization of variance. The method is illustrated and evaluated by means of a worked example from biomedicine in the area of cardiac signal processing. The experimental results show the potential of the approach

[1]  S. Mallat A wavelet tour of signal processing , 1998 .

[2]  Jeffrey M. Hausdorff,et al.  Physionet: Components of a New Research Resource for Complex Physiologic Signals". Circu-lation Vol , 2000 .

[3]  Y. Meyer,et al.  Wavelets and Filter Banks , 1991 .

[4]  J. Kozumplík,et al.  Wavelet transform in electrocardiography--data compression. , 1997, International journal of medical informatics.

[5]  Peter M. Quesada,et al.  Wavelet-based noise removal for biomechanical signals: a comparative study , 2000, IEEE Transactions on Biomedical Engineering.

[6]  Nicola Neretti,et al.  An adaptive approach to wavelet filters design , 2002, Proceedings of the 12th IEEE Workshop on Neural Networks for Signal Processing.

[7]  C. Li,et al.  Detection of ECG characteristic points using wavelet transforms. , 1995, IEEE transactions on bio-medical engineering.