Title :
On the improved correlative prediction scheme for aliased electrocardiogram (ECG) data compression
Author_Institution :
Dept. of Electr. & Comput. Eng., Univ. of Arizona, Tucson, AZ, USA
fDate :
Aug. 28 2012-Sept. 1 2012
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.
Keywords :
data compression; electrocardiography; medical signal processing; wavelet transforms; GM(1,1) model; adjacent QRS waveform correlative characteristics; aliased electrocardiogram data compression; compression ratio; distortion rates; grey predictions; lifting wavelet transform; periodical ECG waves; twin-R correlation prediction; Correlation; Data compression; Data models; Electrocardiography; Predictive models; Wavelet transforms; Data compression; GM(1, 1) model; correlative prediction; electrocardiogram (ECG); lifting wavelet transform (LWT); Electrocardiography; Models, Theoretical; Predictive Value of Tests;
Conference_Titel :
Engineering in Medicine and Biology Society (EMBC), 2012 Annual International Conference of the IEEE
Conference_Location :
San Diego, CA
Print_ISBN :
978-1-4244-4119-8
Electronic_ISBN :
1557-170X
DOI :
10.1109/EMBC.2012.6347405
