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High efficient ECG compression based on reversible round-off non-recursive 1-D discrete periodized wavelet transform.

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

  • 1Institute of Engineering Science and Technology, National Kaohsiung First University of Science and Technology, Taiwan; Department of Information Management, Tzu Hui Institute of Technology, Taiwan.

Medical Engineering & Physics
|February 20, 2007
PubMed
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This study introduces a new wavelet transform and quantization method for electrocardiogram (ECG) data compression. The approach effectively reduces errors and improves compression ratios for better medical data analysis.

Area of Science:

  • Biomedical Engineering
  • Signal Processing
  • Data Compression

Background:

  • Wavelet-based ECG compression methods are hindered by error propagation and word-length growth.
  • Existing methods often struggle with maintaining signal integrity and achieving high compression ratios.

Purpose of the Study:

  • To develop novel techniques to overcome error propagation and word-length growth in wavelet-based ECG compression.
  • To enhance the compression performance and reversibility of ECG data processing.

Main Methods:

  • Development of a non-recursive 1-D discrete periodized wavelet transform (1-D NRDPWT).
  • Application of a reversible round-off linear transformation (RROLT) theorem to achieve reversible octave coefficients with minimum dynamic range (MDR).
  • Implementation of a non-linear quantization algorithm with adaptive decimal quantization scales for high and low octave coefficients.

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Main Results:

  • The 1-D NRDPWT effectively resists truncation error propagation during decomposition.
  • The RROLT theorem suppresses word-length growth, enabling reversible coefficients.
  • Evaluations using the MIT-BIH arrhythmia database demonstrate superior compression performance, especially at high compression ratios (CR), with favorable Percentage Root-Mean-Square Difference (PRD) and Maximum Amplitude Error (MAE).

Conclusions:

  • The proposed wavelet transform and quantization approach offers a significant improvement in ECG data compression.
  • This method provides superior compression performance and signal fidelity, particularly beneficial for high CR applications in arrhythmia detection.