Multiwavelets for Efficient Data Compression of ECG Data Signals
This paper describes the performance of multiwavelets used for electrocardiogram (ECG) data compression and decompression. The multiwavelet approach was chosen for this work because it can simultaneously provide perfect reconstruction while preserving length (orthogonality), good performance at the boundaries (via linear-phase symmetry), and a high order of approximation (vanishing moments). The paper presents details of several multiwavelets that have been studied. Values for the quality of reconstruction based on Signal to Noise Ratio (SNR), Distortion (D), Percent Root Difference (PRD), and Root Mean Square Error (RMSE) criteria are presented. The results show from the research investigation that the Chui-Lian multiwavelet gives the best result achieving a data compression ratio greater than 20:1 with no loss of fidelity.
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