A Novel Compression Algorithm for Electrocardiogram Signals based on Wavelet Transform and SPIHT
Electrocardiogram (ECG) data compression algorithm
is needed that will reduce the amount of data to be transmitted, stored
and analyzed, but without losing the clinical information content. A
wavelet ECG data codec based on the Set Partitioning In Hierarchical
Trees (SPIHT) compression algorithm is proposed in this paper. The
SPIHT algorithm has achieved notable success in still image coding.
We modified the algorithm for the one-dimensional (1-D) case and
applied it to compression of ECG data.
By this compression method, small percent root mean square
difference (PRD) and high compression ratio with low
implementation complexity are achieved. Experiments on selected
records from the MIT-BIH arrhythmia database revealed that the
proposed codec is significantly more efficient in compression and in
computation than previously proposed ECG compression schemes.
Compression ratios of up to 48:1 for ECG signals lead to acceptable
results for visual inspection.
Discrete Wavelet Transform, ECG compression,SPIHT.