Compression and Decompression of Biomedical Signals

In this work, a novel ECG data compression method is presented which employs set partitioning in hierarchical trees algorithm(SPIHT) on two dimensional electrocardiogram(2D-ECG).The 2D ECG is a two dimensioned array, in which each row of this array indicates one or more period and amplitude[7] normalized ECG beats. When SPIHT algorithm is used to compress one or two-dimensional signals separately it is observed that they achieve precise rate control, progressive quality, high compression ratio and low root mean square[7] difference(PRD).Better results are attained because of the wavelet transform eliminating effect[7] on redundancies between adjacent samples. It is also eliminated in onedimensional ECG-and between adjacent beats by applying 2D wavelet transform. The SPIHT algorithm has achieved prominent success in signal compression. Experiments on selected records of ECG from MIT-BIH arrhythmia database revealed that the proposed algorithm is significantly more efficient for compression.