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A 2-D ECG compression method based on wavelet transform and modified SPIHT.

Shen-Chuan Tai1, Chia-Chun Sun, Wen-Chien Yan

  • 1Department of Electrical Engineering, National Cheng Kung University, Tainan 701, Taiwan, R.O.C. sctai@mail.ncku.edu.tw

IEEE Transactions on Bio-Medical Engineering
|June 28, 2005
PubMed
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This study introduces a novel 2-D wavelet compression method for electrocardiogram (ECG) data, enhancing the SPIHT algorithm. The technique achieves high compression ratios with minimal distortion, proving effective for diverse ECG signals.

Area of Science:

  • Biomedical Engineering
  • Signal Processing
  • Data Compression

Background:

  • Electrocardiogram (ECG) data requires efficient compression for storage and transmission.
  • Existing compression methods may not fully exploit the inherent redundancies in ECG signals.
  • Wavelet transforms are effective for signal decomposition, but 2-D approaches can further leverage signal properties.

Purpose of the Study:

  • To develop a novel two-dimensional (2-D) wavelet-based compression method for ECG data.
  • To improve upon the Set Partitioning in Hierarchical Trees (SPIHT) algorithm for ECG compression.
  • To achieve high compression ratios with low distortion for various ECG morphologies.

Main Methods:

  • A modified SPIHT algorithm was developed, exploiting redundancy in medium- and high-frequency wavelet subbands.

Related Experiment Videos

  • ECG signals were transformed into a 2-D array by cutting and aligning adjacent beats and samples.
  • The 2-D wavelet transform and the modified SPIHT algorithm were applied to the 2-D ECG data.
  • The method was tested using records from the MIT-BIH arrhythmia database.

    • Main Results:

    • The proposed 2-D wavelet-based method achieved a high compression ratio.
    • The compression resulted in relatively low data distortion.
    • The method demonstrated effectiveness across various ECG signal morphologies.

    Conclusions:

    • The novel 2-D wavelet-based ECG compression method, using a modified SPIHT algorithm, is effective.
    • The approach successfully leverages inter-beat and inter-sample redundancies in ECG signals.
    • This technique offers a promising solution for efficient ECG data management.