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ECG denoising and feature extraction techniques - a review.

Haroon Yousuf Mir1, Omkar Singh1

  • 1Department of Electronics and Communication Engineering, National Institute of Technology Srinagar, Srinagar, J&K, India.

Journal of Medical Engineering & Technology
|August 31, 2021
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Summary

This review explores advanced signal processing techniques for electrocardiogram (ECG) denoising and feature extraction. It highlights methods like DWT, EMD, VMD, and EWT to improve cardiac diagnostics by removing noise.

Keywords:
DWTEMDElectrocardiogramVMDartefactsdenoising

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Area of Science:

  • Biomedical Engineering
  • Cardiology
  • Signal Processing

Background:

  • Electrocardiogram (ECG) records heart's bioelectric signals for diagnosing cardiac conditions.
  • Signal noise (e.g., power line interference, EMG) hinders accurate ECG analysis and feature extraction.
  • Noise-free ECG signals are crucial for reliable interpretation and diagnosis.

Purpose of the Study:

  • To review contemporary signal processing techniques for ECG denoising.
  • To evaluate methods for ECG feature extraction.
  • To enhance the accuracy of cardiac diagnostics through improved signal quality.

Main Methods:

  • Review of recent and efficient techniques for ECG denoising and feature extraction.
  • Focus on signal processing methods including Discrete Wavelet Transform (DWT).
  • Evaluation of Empirical Mode Decomposition (EMD), Variational Mode Decomposition (VMD), and Empirical Wavelet Transform (EWT).

Main Results:

  • Identified advanced signal processing techniques capable of effectively denoising ECG signals.
  • Highlighted the utility of DWT, EMD, VMD, and EWT in improving ECG feature extraction.
  • Demonstrated the importance of these techniques for accurate cardiac disease examination.

Conclusions:

  • Advanced signal processing techniques significantly improve ECG signal quality.
  • Effective denoising and feature extraction are vital for accurate cardiology.
  • The reviewed methods offer promising solutions for enhancing ECG analysis and interpretation.