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Related Concept Videos

Electrocardiogram Fundamentals01:28

Electrocardiogram Fundamentals

594
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...
594
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.
Three major waveforms are present in a typical ECG recording: the P wave, the QRS complex, and...
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Correlation between ECG and Cardiac Cycle01:25

Correlation between ECG and Cardiac Cycle

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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...
5.2K
ECG Interpretation of Rhythms01:24

ECG Interpretation of Rhythms

865
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....
865

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Related Experiment Video

Updated: Jul 1, 2025

Real-Time Cardiac Mapping with a Noninvasive Imageless Electrocardiographic Imaging System
10:17

Real-Time Cardiac Mapping with a Noninvasive Imageless Electrocardiographic Imaging System

Published on: April 11, 2025

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Convolutional neural network (CNN)-enabled electrocardiogram (ECG) analysis: a comparison between standard

Andrea Saglietto1,2, Daniele Baccega3,4, Roberto Esposito3

  • 1Division of Cardiology, Cardiovascular and Thoracic Department, "Citta della Salute e della Scienza" Hospital, Turin, Italy.

Frontiers in Cardiovascular Medicine
|March 1, 2024
PubMed
Summary

A lightweight artificial intelligence (AI) model can detect cardiac abnormalities using a single-lead electrocardiogram (ECG). This approach shows promise for widespread cardiac screening, even matching 12-lead ECG performance in some cases.

Keywords:
artificial intelligencedeep learningelectrocardiogramscreeningsingle-lead

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Area of Science:

  • Cardiology
  • Artificial Intelligence
  • Medical Diagnostics

Background:

  • Artificial intelligence (AI) shows potential for early cardiac condition detection via standard 12-lead electrocardiograms (ECGs).
  • The efficacy of AI in identifying cardiac abnormalities from single-lead ECGs requires systematic investigation.

Purpose of the Study:

  • To assess a convolutional neural network's (CNN) performance in identifying ECG abnormalities using a single-lead (D1) setup versus a standard 12-lead setup.

Main Methods:

  • A lightweight CNN was designed to detect 20 cardiac abnormalities using the PTB-XL dataset.
  • The CNN accommodated various lead inputs, comparing standard 12-lead, single-lead D1, and D1 with an additional lead.

Main Results:

  • The single-lead D1 CNN demonstrated satisfactory performance, with an average AUC difference of -8.7% compared to the 12-lead setup.
  • For specific conditions, single-lead D1 achieved comparable diagnostic AUC to the 12-lead ECG.
  • Adding a second lead to D1 reduced the AUC gap to -2.8% versus the 12-lead setup.

Conclusions:

  • A lightweight CNN can predict cardiac abnormalities from single-lead D1 ECGs, similar to 12-lead ECGs.
  • Findings support the use of single-lead ECGs from wearable devices for large-scale cardiac abnormality screening.