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A wavelet transform-based ECG compression method guaranteeing desired signal quality

J Chen1, S Itoh

  • 1Graduate School of Information Systems, University of Electro-Communications, Chofu, Tokyo, Japan. chen@is.uec.ac.jp

IEEE Transactions on Bio-Medical Engineering
|December 3, 1998
PubMed
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This study introduces an efficient electrocardiogram (ECG) compression technique using wavelet transforms and adaptive quantization. The method achieves high compression ratios while maintaining signal accuracy and simplifying implementation.

Area of Science:

  • Biomedical Engineering
  • Signal Processing
  • Medical Informatics

Background:

  • Electrocardiogram (ECG) data analysis is crucial for diagnosing cardiac conditions.
  • Efficient ECG data compression is necessary for storage, transmission, and real-time monitoring.
  • Existing compression methods often face trade-offs between compression ratio, signal fidelity, and computational complexity.

Purpose of the Study:

  • To develop a novel ECG compression method.
  • To achieve high compression ratios while guaranteeing a specific signal distortion level (PRD).
  • To ensure low implementation complexity for practical applications.

Main Methods:

  • Utilizing an orthonormal wavelet transform for signal decomposition.
  • Implementing an adaptive quantization strategy for efficient data representation.

Related Experiment Videos

  • Integrating these techniques to form a cohesive compression algorithm.

    • Main Results:

    • The proposed method achieves high compression ratios.
    • A predetermined percent root mean square difference (PRD) is guaranteed.
    • The algorithm demonstrates low implementation complexity.

    Conclusions:

    • The developed ECG compression method offers a favorable balance between compression performance and signal quality.
    • The technique is suitable for applications requiring efficient ECG data handling.
    • This approach contributes to advancements in digital healthcare and telemedicine.