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Wavelet-based ECG data compression system with linear quality control scheme.

Cheng-Tung Ku¹, King-Chu Hung, Tsung-Ching Wu

¹Department of Digital Content Design, Tzu Hui Institute of Technology, Pingtung 926, Taiwan. chengtung.ku@gmail.com

IEEE Transactions on Bio-Medical Engineering

|February 10, 2010

Summary

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This study introduces a novel wavelet transform for lossy ECG data compression, improving reconstruction quality and offering linear distortion control. The method enhances real-time signal recording and quality control, outperforming existing wavelet techniques.

Area of Science:

Biomedical Engineering
Signal Processing
Data Compression

Background:

Lossy ECG data compression requires maintaining signal quality.
Existing wavelet methods face challenges with real-time recording, nonlinear compression, and quantization error sensitivity.
The word-length-growth (WLG) effect negatively impacts reconstruction quality control.

Purpose of the Study:

To introduce a 1-D reversible nonrecursive discrete periodic wavelet transform for ECG data compression.
To overcome the WLG magnification effect and improve reconstruction quality control.
To develop a linear quantization scheme and prediction model for controlled compression performance.

Main Methods:

Application of 1-D reversible round-off nonrecursive discrete periodic wavelet transform.

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Implementation of error propagation resistance and octave coefficient normalization mechanisms.

Design of a multivariable quantization scheme with a single control variable and a linear quantization scale prediction model.

Main Results:

The proposed method overcomes the WLG magnification effect.
Achieved compression performance with approximate linear distortion characteristics.
Demonstrated superior reconstruction quality control compared to other wavelet-based methods.
Lower computational complexity.

Conclusions:

The novel wavelet transform and quantization scheme provide effective ECG data compression with enhanced quality control.
The system is suitable for real-time ECG signal recoding.
Offers a significant improvement over existing wavelet-based compression techniques.