Quality driven gold washing adaptive vector quantization and its application to ECG data compression

The gold washing (GW) adaptive vector quantization (AVQ) (GW-AVQ) is a relatively new scheme for data compression. The adaptive nature of the algorithm provides the robustness for wide variety of the signals. However, the performance of GW-AVQ highly dependent on a preset parameter called distortion...

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Bibliographic Details
Published in:IEEE transactions on biomedical engineering Vol. 47; no. 2; pp. 209 - 218
Main Authors: MIAOU, S.-G, YEN, H.-L
Format: Journal Article
Language:English
Published: New York, NY IEEE 01.02.2000
Institute of Electrical and Electronics Engineers
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:
Algorithms
Biological and medical sciences
Biomedical measurements
Compression algorithms
Data compression
Distortion measurement
Electrocardiography
Electrocardiography. Vectocardiography
Electrodiagnosis. Electric activity recording
Gold
Investigative techniques, diagnostic techniques (general aspects)
Medical sciences
Root mean square
Sampling methods
Signal encoding
Signal Processing, Computer-Assisted
Vector quantization
Wavelet transforms
Electrodiagnosis
Adaptive algorithm
Vector quantization
Wavelet transformation
Threshold detection
Data compression
Electrocardiography
Myocardium
Distortion
Circulatory system
Performance
Signal analysis
ISSN:0018-9294, 1558-2531
Online Access:Get full text
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Summary:The gold washing (GW) adaptive vector quantization (AVQ) (GW-AVQ) is a relatively new scheme for data compression. The adaptive nature of the algorithm provides the robustness for wide variety of the signals. However, the performance of GW-AVQ highly dependent on a preset parameter called distortion threshold (dth) which must be determined by experience or trial-and-error. The authors propose an algorithm that allows them to assign an initial dth arbitrarily and then automatically progress toward a desired dth according to a specified quality criterion, such as the percent of root mean square difference (PRD) for electrocardiogram (ECG) signals. A theoretical foundation of the algorithm is also presented. This algorithm is particularly useful when multiple GW-AVQ codebooks and, thus, multiple dth's are required in a subband coding framework. Four sets of ECG data with entirely different characteristics are selected from the MIT/BIH database to verify the proposed algorithm. Both the direct GW-AVQ and a wavelet-based GW-AVQ are tested. The results show that a user specified PRD can always be reached regardless of the ECG waveforms, the initial selection of dth or whether a wavelet transform is used in conjunction with the GW-AVQ. An average result of 6% in PRD and 410 bits/s in compressed data rate is obtained with excellent visual quality.
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ISSN:0018-9294
1558-2531
DOI:10.1109/10.821761