2-D compression of ECG signals using ROI mask and conditional entropy coding.
A novel 2-D compression scheme of ECG signals is proposed, which employs 1-D discrete wavelet transform, the region of interest mask, and the conditional entropy coding based on context models. Experimental results on records selected from the Massachusetts Institute of Technology-Beth Israel Hospital arrhythmia database show that the proposed method outperforms some existing compression schemes.
Huang
Boqiang
B
Department of Electronic Engineering, Information Science and Engineering School, Fudan University, Shanghai 200433, China. 071021083@fudan.edu.cn
Wang
Yuanyuan
Y
Chen
Jianhua
J
D000465:Algorithms; D044962:Data Compression / Q000379:methods*; D004562:Electrocardiography / Q000379:methods*; D019277:Entropy; D008955:Models, Cardiovascular