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Related Concept Videos

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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ECG Interpretation of Rhythms01:24

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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.
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Instrumentation Amplifier

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An electrocardiography (ECG) machine is an essential piece of medical equipment used to monitor the electrical activity of the heart. It operates by detecting small electrical changes on the skin that result from the depolarization of the heart muscle during each heartbeat. However, these signals are in the microvolt range and can be easily overwhelmed by noise or interference.
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Exercise Stress Test01:26

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Introduction
Exercise stress testing, commonly known as a treadmill test, is a noninvasive procedure used to evaluate cardiovascular function and diagnose heart conditions.
Definition
An exercise stress test measures the heart's response to exertion using a treadmill or stationary bicycle. Chest electrodes record the heart's electrical activity through an ECG, and blood pressure is monitored regularly.
Purposes
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Electrocardiogram Fundamentals01:28

Electrocardiogram Fundamentals

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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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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
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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...
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An artificial intelligence-enabled ECG algorithm for comprehensive ECG interpretation: Can it pass the 'Turing test'?

Anthony H Kashou1, Siva K Mulpuru2, Abhishek J Deshmukh2

  • 1Department of Medicine, Mayo Clinic, Rochester, Minnesota.

Cardiovascular Digital Health Journal
|March 10, 2022
PubMed
Summary

A new artificial intelligence-enabled electrocardiogram (AI-ECG) algorithm provides comprehensive 12-lead ECG interpretation. This AI-ECG algorithm demonstrates superior performance compared to standard automated programs, closely aligning with expert cardiologist interpretations.

Keywords:
Artificial intelligenceConvolutional neural networkECGECG interpretationElectrocardiogramElectrocardiography

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Area of Science:

  • Cardiology
  • Artificial Intelligence
  • Medical Diagnostics

Background:

  • Electrocardiograms (ECGs) are crucial for diagnosing cardiac conditions.
  • Automated ECG interpretation tools exist but may lack comprehensive accuracy.
  • Human over-reading of automated ECG reports is often necessary.

Purpose of the Study:

  • To develop and evaluate a novel artificial intelligence-enabled ECG (AI-ECG) algorithm.
  • To compare the diagnostic performance of the AI-ECG algorithm against conventional interpretation methods.
  • To assess the AI-ECG algorithm's ability to provide human-like ECG interpretation.

Main Methods:

  • A novel AI-ECG algorithm was developed and trained on approximately 2.5 million 12-lead ECGs.
  • The AI-ECG algorithm's interpretations were compared to a standard automated program and final clinical interpretations.
  • Cardiac electrophysiologists blinded to the interpretation source adjudicated 500 ECGs, classifying edits as ideal, acceptable, or unacceptable.

Main Results:

  • The AI-ECG algorithm required fewer major edits (8.2%) compared to the automated program (13.5%).
  • The AI-ECG algorithm achieved a higher percentage of ideal interpretations (70.5%) than the automated program (63.9%).
  • Both AI-ECG and final clinical interpretations showed higher ideal rates (70.5% and 74.5%) than the automated program.

Conclusions:

  • The AI-ECG algorithm demonstrates superior performance over existing automated ECG interpretation programs.
  • The AI-ECG algorithm more closely approximates expert cardiologist over-read for comprehensive 12-lead ECG interpretation.
  • This AI-ECG technology holds promise for improving the efficiency and accuracy of ECG analysis.