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Related Concept Videos

Electrocardiogram01:29

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An electrocardiogram (ECG or EKG) is a critical diagnostic tool that records the electrical signals produced by the heart during each heartbeat. This recording is achieved through electrodes placed strategically on the arms, legs, and chest. The electrocardiograph amplifies these signals and produces 12 distinct tracings, offering a comprehensive understanding of the heart's electrical activity.
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The electrical signals recorded on an electrocardiogram (ECG) occur before the mechanical processes of contraction and relaxation during the cardiac cycle.
A cardiac action potential originates in the SA node and spreads throughout the atria and the AV node in approximately 0.03 seconds. This results in the P wave in an ECG and triggers atrial contraction. The action potential is then briefly slowed at the AV node, allowing the atria to contract and fill the ventricles with blood before...
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ECG signal denoising via empirical wavelet transform.

Omkar Singh1, Ramesh Kumar Sunkaria2

  • 1Department of Electronics and Communication Engineering, Dr B. R Ambedkar National Institute of Technology, Jalandhar, Punjab, 144 011, India. omkar.parihar@gmail.com.

Australasian Physical & Engineering Sciences in Medicine
|December 31, 2016
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Summary

This study introduces a novel method using empirical wavelet transform (EWT) to effectively remove baseline wander and powerline interference from electrocardiogram (ECG) signals, improving signal quality for analysis.

Keywords:
Baseline wanderElectrocardiogramEmpirical mode decompositionEmpirical wavelet transformPowerline interference

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Area of Science:

  • Biomedical Engineering
  • Signal Processing
  • Medical Informatics

Background:

  • Electrocardiogram (ECG) signals are crucial for diagnosing cardiac conditions.
  • ECG signals are often contaminated by noise, including baseline wander and powerline interference, hindering accurate interpretation.
  • Effective noise reduction is essential for reliable ECG analysis.

Purpose of the Study:

  • To develop and evaluate a new method for reducing baseline wander and powerline interference in ECG signals.
  • To assess the performance of the proposed method against existing filtering techniques.
  • To enhance the quality of ECG signals for improved diagnostic accuracy.

Main Methods:

  • The study utilizes the Empirical Wavelet Transform (EWT), a novel signal processing technique.
  • EWT is employed to decompose the ECG signal into its constituent modes.
  • The performance of EWT is compared with standard linear filters and Empirical Mode Decomposition (EMD).

Main Results:

  • The proposed EWT-based method demonstrates superior performance in filtering both baseline wander and powerline interference.
  • EWT effectively isolates and removes noise components while preserving the integrity of the ECG signal.
  • Quantitative and qualitative comparisons show EWT outperforms traditional methods.

Conclusions:

  • Empirical Wavelet Transform (EWT) offers a powerful and effective solution for cleaning noisy ECG signals.
  • This technique can significantly improve the reliability of ECG data for clinical applications.
  • The findings suggest EWT as a promising tool for biomedical signal processing.