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Data processing of stress ECGs using discrete cosine transform

J S Paul1, M R Reddy, V J Kumar

  • 1Department of Electrical Engineering, Indian Institute of Technology, Madras, India.

Computers in Biology and Medicine
|January 8, 1999
PubMed
Summary
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This study introduces a two-step discrete cosine transform (DCT) method using singular value decomposition (SVD) for enhanced electrocardiogram (ECG) signal processing. The technique effectively suppresses noise and removes baseline wander, preserving crucial ECG waveform features.

Area of Science:

  • Biomedical Engineering
  • Signal Processing
  • Cardiology

Background:

  • Electrocardiogram (ECG) analysis requires high signal-to-noise ratio (SNR) for accurate interpretation.
  • Artifacts from respiration and movement degrade ECG signal quality.
  • Existing signal processing methods often struggle to balance noise reduction with feature preservation.

Purpose of the Study:

  • To develop and evaluate novel signal processing techniques for stress ECG analysis.
  • To improve noise suppression and baseline wander removal in ECG recordings.
  • To assess the effectiveness of the discrete cosine transform (DCT) in conjunction with singular value decomposition (SVD).

Main Methods:

  • A two-step noise suppression algorithm utilizing the discrete cosine transform (DCT).

Related Experiment Videos

  • Inclusion of singular value decomposition (SVD) smoothing in both the transform and time domains.
  • Comparison of mean square error (MSE) with ideal Wiener filter performance using DCT.

    • Main Results:

    • The proposed DCT-based algorithm effectively suppresses noise and removes baseline wander from ECG signals.
    • The first SVD smoothing step in the transform domain approximates ideal Wiener filtering.
    • A second SVD smoothing step in the time domain further refines the signal, approaching minimum mean square error (MMSE).

    Conclusions:

    • The combined DCT and SVD approach achieves near-perfect reproduction of noise-free ECG signals.
    • The method preserves the essential morphological features of the original ECG waveform.
    • This technique offers a robust solution for improving the quality of stress ECG analysis.