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Fast ECG data compression algorithms suitable for microprocessor systems
X B Huang1, M J English, R Vincent
1Graduate Division of Biomedical Engineering, University of Sussex, Brighton, UK.
Journal of Biomedical Engineering
|January 1, 1992
Summary
Two new ECG data compression algorithms, MSAPA and CSAPA, offer over 5:1 compression with less than 3.5% PRD. CSAPA specifically preserves critical ST segment details for ischemia diagnosis.
Area of Science:
- Biomedical Engineering
- Signal Processing
- Cardiology
Background:
- ECG data compression is crucial for efficient ECG analysis and storage.
- Existing algorithms have limitations in multichannel data reduction and ST segment preservation.
Purpose of the Study:
- To introduce two novel ECG data compression algorithms, MSAPA and CSAPA, based on the Scan-Along Polygonal Approximation (SAPA).
- To evaluate their effectiveness for multichannel ECG data reduction in microprocessor-based systems.
- To assess their ability to preserve diagnostically important ST segment information.
Main Methods:
- Modification of SAPA (MSAPA) using integer division table searching for accelerated data reduction.
- Combination of MSAPA with a turning-point (TP) algorithm (CSAPA) to enhance ST segment signal preservation.
- Evaluation of compression ratio, percent root mean square difference (PRD), and execution time.
Main Results:
- Achieved a compression ratio exceeding 5:1.
- Maintained a PRD of less than 3.5% compared to the original ECG signal.
- MSAPA demonstrated a maximum execution time of approximately 50 microseconds per data point.
- CSAPA successfully retained ST segment details vital for ischemia diagnosis.
Conclusions:
- MSAPA and CSAPA are efficient algorithms for multichannel ECG data compression on microprocessor systems.
- CSAPA offers superior ST segment preservation, making it valuable for diagnosing conditions like ischemia.
- The developed algorithms balance compression efficiency with diagnostic signal integrity.