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Electrocardiogram01:29

Electrocardiogram

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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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Introduction
An electrocardiogram (ECG) is a diagnostic tool for identifying cardiac conditions such as arrhythmias, conduction abnormalities, and myocardial ischemia.
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In signal processing, signals are classified based on various characteristics: continuous-time versus discrete-time, periodic versus aperiodic, analog versus digital, and causal versus noncausal. Each category highlights distinct properties crucial for understanding and manipulating signals.
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The normal cardiac rhythm is a synchronized electrical activity that facilitates the regular and coordinated contraction of the heart muscle. This process is essential for efficient blood circulation throughout the body. The fundamental elements involved in establishing and maintaining this rhythm include the unique electrical properties of cardiac muscle cells, the sinoatrial (SA) node's pacemaker function, the specialized conducting system, and the ionic mechanisms underlying each phase...
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Quantification of Global Diastolic Function by Kinematic Modeling-based Analysis of Transmitral Flow via the Parametrized Diastolic Filling Formalism
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Electrocardiogram Signals Denoising Using Improved Variational Mode Decomposition.

Vikas Malhotra1, Mandeep Kaur Sandhu1

  • 1Department of Electronic and Communication Engineering, University School of Engineering and Technology, Rayat Bahra University, Mohali, Punjab, India.

Journal of Medical Signals and Sensors
|July 16, 2021
PubMed
Summary

This study introduces an improved variational mode decomposition (IVMD) method to effectively remove noise from electrocardiogram (ECG) signals. The IVMD technique significantly enhances signal quality compared to traditional methods, improving diagnostic accuracy.

Keywords:
Denoisingelectrocardiogramvariational mode decomposition

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Area of Science:

  • Biomedical Engineering
  • Signal Processing

Background:

  • Electrocardiogram (ECG) signals are crucial for diagnosing heart conditions and assessing mental stress.
  • ECG data are often corrupted by noise, including baseline wandering, muscle artifacts, and power line interference.
  • Effective noise removal is essential for accurate ECG signal interpretation.

Purpose of the Study:

  • To develop and evaluate an improved variational mode decomposition (IVMD) method for denoising ECG signals.
  • To compare the performance of the proposed IVMD technique against the traditional variational mode decomposition (VMD) method.

Main Methods:

  • The study employed an improved variational mode decomposition (IVMD) method, featuring adaptive window size adjustment based on weighted signal amplitude.
  • ECG data were acquired from 10 subjects and the MIT-BIH database.

Main Results:

  • The IVMD method achieved a highest signal-to-noise ratio (SNR) of 83db.
  • Traditional VMD yielded a highest SNR of 42db.
  • Performance was quantitatively assessed using metrics like mean square error, percentage root mean square difference, SNR, and correlation coefficient.

Conclusions:

  • The proposed IVMD technique demonstrates superior performance in denoising ECG signals compared to the traditional VMD method.
  • IVMD offers a more effective approach for cleaning ECG data, enhancing its diagnostic utility.