On the improved correlative prediction scheme for aliased electrocardiogram (ECG) data compression
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Xin_EMBC'2012_ECGPaper.pdf
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Final Accepted Manuscript
Affiliation
Univ Arizona, Dept Elect & Comp EngnIssue Date
2012-11-12Metadata
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IEEECitation
Gao, X. (2012, August). On the improved correlative prediction scheme for aliased electrocardiogram (ECG) data compression. In 2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society (pp. 6180-6183). IEEE.Journal
2012 Annual International Conference of the IEEE Engineering in Medicine and Biology SocietyRights
© 2012 IEEE.Collection Information
This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at repository@u.library.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.ISSN
978-1-4244-4119-8978-1-4577-1787-1