Key result
Modified SPIHT algorithm reduces ECG compression time vs earlier versions while controlling signal degradation.
A modified SPIHT algorithm provides efficient ECG signal compression with minimal computational time, making it suitable for telemedicine applications.
Modified SPIHT may enhance ECG compression efficiency; leaves open prospective clinical validation before any workflow adoption.
In this paper, an improved method for electrocardiogram (ECG) signal compression using Set Partitioning in Hierarchical Trees (SPIHT) algorithm is proposed. ECG signals are compressed based on different transform such as discrete cosine transform and discrete wavelet transform with modified SPIHT. The modified SPIHT algorithm yields good compression with controlled quantity of signal degradation and requires computational time as compared to earlier published SPIHT algorithms. The proposed algorithm is suitable for the ECG signal compression for telemedicine or e-health system due to minimum computational time.
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Kumar et al. (2014) studied ECG signal compression. Modified SPIHT algorithm vs. Earlier published SPIHT algorithms was evaluated on Compression quality and computational time. The modified SPIHT algorithm for ECG signal compression yielded good compression with controlled signal degradation and required less computational time compared to earlier SPIHT algorithms.
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