Wavelet-based lossy-to-lossless ECG compression in a unified vector quantization framework.
In a prior work, a wavelet-based vector quantization (VQ) approach was proposed to perform lossy compression of electrocardiogram (ECG) signals. In this paper, we investigate and fix its coding inefficiency problem in lossless compression and extend it to allow both lossy and lossless compression in a unified coding framework. The well-known 9/7 filters and 5/3 integer filters are used to implement the wavelet transform (WT) for lossy and lossless compression, respectively. The codebook updating mechanism, originally designed for lossy compression, is modified to allow lossless compression as well. In addition, a new and cost-effective coding strategy is proposed to enhance the coding efficiency of set partitioning in hierarchical tree (SPIHT) at the less significant bit representation of a WT coefficient. ECG records from the MIT/BIH Arrhythmia and European ST-T Databases are selected as test data. In terms of the coding efficiency for lossless compression, experimental results show that the proposed codec improves the direct SPIHT approach and the prior work by about 33% and 26%, respectively.
Miaou
Shaou-Gang
SG
Multimedia Computing and Telecommunications Laboratory, Department of Electronic Engineering, Chung Yuan Christian University, Chung-Li, 32023 Taiwan, ROC. miaou@wavelet.el.cycu.edu.tw
Chao
Shu-Nien
SN
D000465:Algorithms; D001145:Arrhythmias, Cardiac / Q000175:diagnosis* / Q000503:physiopathology*; D044962:Data Compression / Q000379:methods*; D004562:Electrocardiography / Q000379:methods*; D006801:Humans; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D012815:Signal Processing, Computer-Assisted