title: 2-D compression of ECG signals using ROI mask and conditional entropy coding.
abstract: 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.
authors.affiliation: Department of Electronic Engineering, Information Science and Engineering School, Fudan University, Shanghai 200433, China. 071021083@fudan.edu.cn
authors.forename: Boqiang
authors.initials: B
authors.lastname: Huang
authors.forename: Yuanyuan
authors.initials: Y
authors.lastname: Wang
authors.forename: Jianhua
authors.initials: J
authors.lastname: Chen
mesh_terms: D000465:Algorithms; D044962:Data Compression / Q000379:methods*; D004562:Electrocardiography / Q000379:methods*; D019277:Entropy; D008955:Models, Cardiovascular