On the Improved Correlative Prediction Scheme for Aliased Electrocardiogram (ECG) Data Compression

被引：0
|
作者：
Gao, Xin [1 ]
机构：
[1] Univ Arizona, Dept Elect & Comp Engn, Tucson, AZ 85721 USA
来源：
2012 ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY (EMBC) | 2012年
关键词：
Data compression; correlative prediction; electrocardiogram (ECG); lifting wavelet transform (LWT); GM (1,1) model;
D O I：
暂无
中图分类号：
R318 [生物医学工程];
学科分类号：
0831 ;
摘要：
An improved scheme for aliased electrocardiogram (ECG) data compression has been constructed, where the predictor exploits the correlative characteristics of adjacent QRS waveforms. The twin-R correlation prediction and lifting wavelet transform (LWT) for periodical ECG waves exhibits feasibility and high efficiency to achieve lower distortion rates with realizable compression ratio (CR); grey predictions via GM(1, 1) model have been adopted to evaluate the parametric performance for ECG data compression. Simulation results illuminate the validity of our approach.
引用
收藏
页码：6180 / 6183
页数：4
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