Multiresolution representation and analysis of ECG waveforms

A new pattern recognition method is introduced for the multiresolution representation and analysis of electrocardiogram (ECG) waveforms. The multiresolution representation is based on filtering the curvature of the curve with continuum of Gaussian filters where Gaussian standard deviation increases, and on extracting of extrema points in filtered versions of the curvature (scale-space filtering). The original curve is then segmented at each scale into linear parts with regard to the extracted extrema points. After segmentation and linking segments between scales, shape is represented qualitatively in a hierarchical tree form holding information on coarser and finer details of shape. Different methods of tree form analysis can be applied to data compression, classification of heart beats or fine structure analysis. The fast computation scheme and transformation into hierarchical structure are described. In addition to the method of representation, a data compression method is proposed. Comparison to the AZTEC data compression method is given