Key result
An ECG signal compression technique based on Slantlet transform provided better reconstruction and compression performance compared to wavelet and discrete cosine transform techniques.
Why the study?
Does Slantlet transform improve ECG signal compression and reconstruction fidelity compared to wavelet and discrete cosine transform techniques?
Does Slantlet transform improve ECG signal compression and reconstruction fidelity compared to wavelet and discrete cosine transform techniques?
Slantlet transform provides superior ECG signal compression and reconstruction fidelity compared to traditional wavelet and discrete cosine transform techniques.
In this paper, an ECG signal compression technique is presented based on Slantlet transform with different thresholding functions. The presented compression method is exploited the uniform quantization (UQ) methods with different thresholding criteria on slantlet coefficients of ECG signal. This technique the returned the better reconstruction from compressed data as compare to wavelet and discrete cosine transform technique due to better energy compaction efficiency. A detail analysis has been presented for compression and signal retrieval efficiency along with evaluation of thresholding criteria. The presented technique is tested with different ECG signal obtained from MIT-BIH arrhythmia database. The simulation and experimental results clearly illustrate the slantlet transform gives better performance in term of fidelity assessments in term of CR, SNR and PRD with better compression as compared to contemporary techniques.
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Swarnkar et al. (2017) studied ECG signal compression. Slantlet transform with different thresholding functions vs. Wavelet and discrete cosine transform techniques was evaluated on Fidelity assessments in terms of CR, SNR and PRD. An ECG signal compression technique based on Slantlet transform provided better reconstruction and compression performance compared to wavelet and discrete cosine transform techniques.
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