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A novel ECG data compression method based on nonrecursive discrete periodized wavelet transform.

Cheng-Tung Ku¹, Huan-Sheng Wang, King-Chu Hung

¹Institute of Engineering Science and Technology, National Kaohsiung First University of Science and Technology, Taiwan, ROC.

IEEE Transactions on Bio-Medical Engineering

|December 13, 2006

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A new electrocardiogram (ECG) data compression method uses full wavelet coefficients and a reversible transform for high compression ratios. This novel approach improves upon existing methods, offering better performance for ECG analysis.

Area of Science:

Biomedical Engineering
Signal Processing
Data Compression

Background:

Electrocardiogram (ECG) data requires efficient compression for storage and transmission.
Existing compression methods may suffer from error propagation or limited compression ratios.

Purpose of the Study:

To propose a novel ECG data compression method utilizing full wavelet coefficients.
To develop a reversible wavelet transform and a nonlinear quantization algorithm for improved compression.

Main Methods:

Implementation of a reversible round-off nonrecursive one-dimensional (1-D) discrete periodized wavelet transform (1-D NRDPWT).
Development of a nonlinear word length reduction algorithm for efficient quantization of wavelet coefficients.
Evaluation using the MIT-BIH arrhythmia database, assessing compression ratio (CR) and percentage root mean square difference (PRD).

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Main Results:

The proposed method achieves high compression ratios with minimal register word length.
The nonlinear quantization algorithm effectively handles high and low octave coefficients.
Significant improvements in PRD were observed compared to the SPIHT scheme: 14.95% for CR 4-12 and 17.6% for CR 14-20.

Conclusions:

The novel ECG compression method offers superior performance in terms of PRD and CR.
The use of full wavelet coefficients and a reversible transform enhances compression efficiency and accuracy.
This method presents a promising advancement for ECG data processing and analysis.