Beat reordering for optimal electrocardiogram signal compression using SPIHT

An effective electrocardiogram (ECG) signal compression method based on two-dimensional wavelet transform which employs set partitioning in hierarchical trees (SPIHT) and beat reordering technique is presented. This method utilizes the redundancy between adjacent samples and adjacent beats. Beat reordering rearranges beat order in 2D ECG array based on the similarity between adjacent beats. This rearrangement reduces variances between adjacent beats so that the 2D ECG array contains less high frequency component. The experiments on two datasets from MIT-BIH arrhythmia database revealed that the proposed method is more efficient for ECG signal compression in comparison with several previous proposed methods in literature. The experimental results show that the proposed method yields relatively low distortion at high compression rate.