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Data compression applied to dynamic electrocardiography.

M Bertinelli, A Catelli, C Combi

    Medical & Biological Engineering & Computing
    |January 1, 1989
    PubMed
    Summary
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    We evaluated ECG compression techniques on the BIH/MIT Arrhythmias database. Methods like prediction and sample skipping achieved compression ratios up to 1:5 with acceptable error levels.

    Area of Science:

    • Biomedical Engineering
    • Signal Processing
    • Data Compression

    Background:

    • Electrocardiogram (ECG) data requires efficient compression for storage and transmission.
    • The BIH/MIT Arrhythmias database is a standard benchmark for evaluating ECG analysis algorithms.

    Purpose of the Study:

    • To assess the effectiveness of different ECG compression techniques.
    • To quantify compression ratios and error types for various methods.

    Main Methods:

    • Applied method of differences, compression by prediction, and sample skipping.
    • Evaluated amplitude, amplitude and delay, and area errors.
    • Utilized Huffman encoding for data compression.

    Main Results:

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  • Method of differences and compression by prediction achieved an average code length of approximately 4 bits/sample.
  • Sample skipping methods yielded variable compression ratios based on error thresholds.
  • A compression ratio slightly less than 1:5 was achieved with sample skipping under limited error thresholds.

    • Conclusions:

    • ECG compression techniques offer significant data reduction for the BIH/MIT Arrhythmias database.
    • Sample skipping provides a flexible approach to ECG compression, balancing ratio and error.
    • The tested methods demonstrate potential for efficient ECG data management.