Key result
A modified SPIHT wavelet compression method with two additional steps achieved higher compression ratio and lower percentage rms difference for ECG signals compared to the existing technique.
A modified SPIHT wavelet compression method improves ECG signal compression ratio and reduces error without compromising computational efficiency.
May improve ECG data transmission in bandwidth-limited settings; leaves open clinical validation in prospective trials.
This paper presents a modified version of Set Partitioning In Hierarchical Trees (SPIHT) wavelet compression method, which has been developed for ECG signal compression. Two more steps in the existing technique have been added to achieve higher compression ratio (CR) and lower percentage rms difference (PRD). The method has been tested on selected records from the MIT-BIH arrhythmia database. Even with two more steps, the method retains its simplicity, computational efficiency and self-adaptiveness, without compromising on any other performance parameter.
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Singh et al. (2007) studied ECG signal compression. Modified Set Partitioning In Hierarchical Trees (SPIHT) wavelet compression method vs. Existing SPIHT technique was evaluated on Compression ratio (CR) and percentage rms difference (PRD). A modified SPIHT wavelet compression method with two additional steps achieved higher compression ratio and lower percentage rms difference for ECG signals compared to the existing technique.
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