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Decomposition of ECG by linear filtering.

I S Murthy1, U C Niranjan

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

Computers in Biology and Medicine
|January 1, 1992
PubMed
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This study introduces a simple method using discrete cosine transform (DCT) to separate electrocardiogram (ECG) signals into their component waves. The technique proved effective for analyzing ECGs with arrhythmias, though small P waves showed higher differences.

Area of Science:

  • Biomedical Engineering
  • Signal Processing
  • Cardiology

Background:

  • Electrocardiogram (ECG) signals are crucial for diagnosing heart conditions.
  • Accurate delineation of ECG component waves (P, QRS, T) is essential for detailed analysis.
  • Existing methods for ECG wave delineation can be complex or computationally intensive.

Purpose of the Study:

  • To develop a simple and effective method for delineating component waves of an electrocardiogram (ECG) signal.
  • To utilize the properties of the discrete cosine transform (DCT) for ECG signal decomposition.
  • To evaluate the performance of the proposed method in analyzing ECG signals with various arrhythmias.

Main Methods:

  • A novel method employing discrete cosine transform (DCT) for ECG signal analysis.

Related Experiment Videos

  • Convolution of the DCT-transformed signal with derived filters.
  • Obtaining component waves through inverse discrete cosine transform (IDCT).
  • Filters are adaptively derived from the time-domain ECG signal itself.

    • Main Results:

    • The proposed method successfully delineates ECG signals into component waves.
    • Qualitative and quantitative analyses demonstrate satisfactory performance on continuous ECG strips with arrhythmias.
    • The P wave, characterized by small amplitude, exhibited a higher percentage root mean square difference (PRD) compared to larger waves.

    Conclusions:

    • The DCT-based method offers a simple and effective approach for ECG component wave delineation.
    • The technique is robust for analyzing ECG signals, including those with arrhythmias.
    • Further refinement may be needed to improve the accuracy for small-amplitude waves like the P wave.