title: ECG compression using wavelet transform and particle swarm optimization.
abstract: A new adaptive thresholding mechanism to determine the significant wavelet coefficients of an electrocardiogram (ECG) signal is proposed. It is based on estimating thresholds for different sub-bands using the concept of energy packing efficiency (EPE). Then thresholds are optimized using the particle swarm optimization (PSO) algorithm to achieve a target compression ratio with minimum distortion. Simulation results on several records taken from the MIT-BIH Arrhythmia database show that the PSO converges exactly to the target compression after four iterations while the cost function achieved its minimum value after six iterations. Compared to previously published schemes, lower distortions are achieved for the same compression ratios.
authors.affiliation: Communication Engineering Department, Yarmouk University, Irbid, Jordan. ashamali@yu.edu.jo
authors.forename: A
authors.initials: A
authors.lastname: Alshamali
authors.forename: M
authors.initials: M
authors.lastname: Al-Aqil
mesh_terms: D044962:Data Compression / Q000379:methods*; D004562:Electrocardiography / Q000379:methods*