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Conf Proc IEEE Eng Med Biol Soc. 2012;2012:6180-3. doi: 10.1109/EMBC.2012.6347405.

On the improved correlative prediction scheme for aliased electrocardiogram (ECG) data compression.

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1
Department of Electrical and Computer Engineering, The University of Arizona, Tucson, AZ 85721, USA. xgao1985@email.arizona.edu

Abstract

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.

PMID:
23367340
DOI:
10.1109/EMBC.2012.6347405
[Indexed for MEDLINE]
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