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Related Concept Videos

Electrocardiogram01:29

Electrocardiogram

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.
Three major waveforms are present in a typical ECG recording: the P wave, the QRS complex, and the T...
Electrocardiogram Fundamentals01:28

Electrocardiogram Fundamentals

Introduction
An electrocardiogram (ECG) is a diagnostic tool for identifying cardiac conditions such as arrhythmias, conduction abnormalities, and myocardial ischemia.
Definition
An electrocardiogram (ECG) visualizes the heart's electrical activity by tracing the electrical movement associated with each heartbeat on a graph or monitor. As the heart beats, an electrical wave passes through it, correlating with the cardiac cycle events.
Parts of an ECG
An ECG utilizes electrodes on the skin to...
Correlation between ECG and Cardiac Cycle01:25

Correlation between ECG and Cardiac Cycle

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...
ECG Interpretation of Rhythms01:24

ECG Interpretation of Rhythms

An electrocardiogram (ECG)graphically represents the heart's electrical activity on ECG paper or a monitor.
Components of the Electrocardiogram
The primary components of a normal ECG waveform in Normal sinus rhythm(NSR) include the P wave, PR interval, QRS complex, ST segment, T wave, and occasionally a U wave.
ECG waveforms are divided by vertical and horizontal lines at standard intervals.
The horizontal axis measures time and rate, and the vertical axis measures amplitude or voltage. When...

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Related Experiment Video

Updated: Jun 13, 2026

Real-Time Electrocardiogram Monitoring During Treadmill Training in Mice
04:45

Real-Time Electrocardiogram Monitoring During Treadmill Training in Mice

Published on: May 5, 2022

An Adaptive Run Length Encoding method for the compression of electrocardiograms.

Cristiano M Agulhari1, Ivanil S Bonatti, Pedro L D Peres

  • 1School of Electrical and Computer Engineering, University of Campinas - Unicamp, 13083-852, SP. agulhari@dt.fee.unicamp.br

Medical Engineering & Physics
|April 27, 2010
PubMed
Summary

This study introduces an advanced wavelet-based compression method for electrocardiogram (ECG) signals. The novel approach minimizes distortion by optimizing wavelet selection and efficiently encodes significant data, improving compression efficiency.

Related Experiment Videos

Last Updated: Jun 13, 2026

Real-Time Electrocardiogram Monitoring During Treadmill Training in Mice
04:45

Real-Time Electrocardiogram Monitoring During Treadmill Training in Mice

Published on: May 5, 2022

Area of Science:

  • Biomedical Engineering
  • Signal Processing
  • Data Compression

Background:

  • Electrocardiogram (ECG) signal compression is crucial for efficient data storage and transmission.
  • Existing compression methods may not optimally balance compression ratio and signal distortion.

Purpose of the Study:

  • To propose a novel wavelet-based compression method for ECG signals.
  • To minimize compression distortion by selecting an optimal wavelet for each signal.
  • To enhance the efficiency of ECG data encoding.

Main Methods:

  • Developed a compression method utilizing wavelet transforms.
  • Employed an optimization problem to determine the optimal scaling filter for wavelet determination.
  • Retained only significant wavelet coefficients based on a pre-specified distortion measure.
  • Encoded coefficient positions and values using an improved Run Length Encoding (RLE) technique.

Main Results:

  • The proposed method achieves efficient compression of ECG signals.
  • Optimized wavelet selection minimizes signal distortion.
  • The improved RLE encoding enhances the overall compression performance.
  • Experimental comparisons demonstrate the method's effectiveness against existing techniques.

Conclusions:

  • The proposed wavelet-based compression method offers an efficient solution for ECG data.
  • The technique effectively minimizes distortion while maintaining high compression ratios.
  • This approach has significant potential for applications in medical data management and telemedicine.