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ECG data compression using cut and align beats approach and 2-D transforms.

H Lee1, K M Buckley

  • 1University of Minnesota, Department of Electrical Engineering, Minneapolis 55455, USA. hwlee@ece.umn.edu

IEEE Transactions on Bio-Medical Engineering
|May 7, 1999
PubMed
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This study introduces a novel two-dimensional (2-D) transform method for electrocardiogram (ECG) data compression. The new approach significantly improves compression ratios compared to 1-D methods while maintaining data accuracy.

Area of Science:

  • Biomedical Engineering
  • Signal Processing
  • Medical Informatics

Background:

  • Electrocardiogram (ECG) data requires efficient compression for storage and transmission.
  • Existing one-dimensional (1-D) compression methods have limitations in achieving high compression ratios.
  • ECG signals exhibit inherent redundancies both within and between heartbeats.

Purpose of the Study:

  • To develop and evaluate a novel two-dimensional (2-D) transform-based method for ECG data compression.
  • To leverage inter-beat and intra-beat redundancies in ECG signals for enhanced compression.
  • To compare the performance of the proposed 2-D compression method against existing 1-D techniques.

Main Methods:

  • A 2-D transform approach was applied to ECG data.

Related Experiment Videos

  • ECG signal sequences were segmented and beat-aligned to form a 2-D data array.
  • Two-dimensional Discrete Cosine Transform (2-D DCT) was employed as a specific 2-D compression technique.

    • Main Results:

    • The 2-D transform method demonstrated substantial improvements in compression ratio.
    • Performance was evaluated using data from the MIT-BIH arrhythmia and Medtronic databases.
    • Comparable or better percent root-mean-square difference (PRD) was achieved compared to 1-D methods.

    Conclusions:

    • The proposed 2-D transform method offers a significant advancement in ECG data compression.
    • This technique effectively exploits signal redundancies for superior compression efficiency.
    • The 2-D DCT-based approach provides a promising solution for medical data compression challenges.