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System identification for the ECG using CZT.

U C Niranjan1, I S Murthy

  • 1Department of Electrical Engineering, Indian Institute of Science, Bangalore.

Computers and Biomedical Research, an International Journal
|October 1, 1992
PubMed
Summary
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This study introduces a novel method for extracting electrocardiogram (ECG) parameters using system identification on DCT-transformed signals. The approach enables accurate R-R interval determination and achieves significant data compression for improved ECG analysis.

Area of Science:

  • Biomedical Engineering
  • Signal Processing
  • Cardiology

Background:

  • Electrocardiogram (ECG) analysis is crucial for diagnosing cardiac conditions.
  • Extracting clinically relevant parameters from ECG signals efficiently remains a challenge.
  • Existing methods may lack precision or require substantial computational resources.

Purpose of the Study:

  • To develop a new, efficient method for extracting clinically useful parameters from ECG signals.
  • To establish a direct relationship between model singularities and significant time-domain ECG features.
  • To enable accurate determination of the R-R interval for rhythm analysis.

Main Methods:

  • Utilized the Chirp Z-Transform (CZT) system identification technique on Discrete Cosine Transform (DCT)-transformed ECG signals.

Related Experiment Videos

  • Employed complex cepstrum analysis to identify and mitigate the influence of zeros outside the unit circle.
  • Applied the method to analyze numerous continuous ECG data strips.

    • Main Results:

    • Established a one-to-one correspondence between model singularities and significant points in the time-domain ECG signal.
    • Successfully determined the R-R interval, essential for heart rhythm analysis.
    • Achieved a substantial data compression ratio of 1:10, reducing data storage and transmission requirements.
    • Demonstrated the method's efficacy through analysis of extensive ECG data.

    Conclusions:

    • The proposed CZT-based system identification on DCT-transformed ECG signals offers an effective approach for parameter extraction.
    • This method accurately identifies key ECG features and facilitates R-R interval calculation.
    • Significant data compression achieved enhances the practicality of ECG data analysis and management.