Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Electrocardiogram01:29

Electrocardiogram

1.7K
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...
1.7K
Pulse rhythm01:30

Pulse rhythm

725
Pulse rhythm refers to the pattern of pulsations within specific intervals, offering valuable insights into the regularity or irregularity of the heart's beats as observed through the pattern of pulsation within specific intervals. A regular pulse exhibits a consistent heart rate with uniform waveforms and pulsation force, variations of which can be classified as normal, weak, or bounding.
Conversely, an irregular pulse pattern is termed dysrhythmia, stemming from disruptions in cardiac...
725
Exercise Stress Test01:26

Exercise Stress Test

144
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
144
ECG Interpretation of Rhythms01:24

ECG Interpretation of Rhythms

312
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....
312
Electrocardiogram Fundamentals01:28

Electrocardiogram Fundamentals

450
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...
450
Correlation between ECG and Cardiac Cycle01:25

Correlation between ECG and Cardiac Cycle

2.9K
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...
2.9K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Transformer-DAPT: AI-based dynamic assessment of ischemic and bleeding risks in patients on DAPT following PCI.

NPJ digital medicine·2026
Same author

Integrating molecular and conventional diagnostics in native vertebral osteomyelitis: a narrative review.

Journal of bone and joint infection·2026
Same author

Defining Success and Failure In Prosthetic Joint Infections: A Meta-epidemiologic Study Toward A Core Outcome Set.

Open forum infectious diseases·2026
Same author

Maternal Mortality and Cardio-Kidney-Metabolic Risk Factors Across High-Income Countries.

JACC. Advances·2026
Same author

AI-augmented ECG for pre-echocardiography triage: a tool to optimize cardiac imaging utilization.

European heart journal. Digital health·2026
Same author

Multispline catheter mapping of the coronary ostia to guide aortic root ablation.

Revista espanola de cardiologia (English ed.)·2026

Related Experiment Video

Updated: May 15, 2025

A High-Throughput Multiplexed Screening for Type 1 Diabetes, Celiac Diseases, and COVID-19
06:46

A High-Throughput Multiplexed Screening for Type 1 Diabetes, Celiac Diseases, and COVID-19

Published on: July 5, 2022

2.7K

RApid Throughput Screening for Asymptomatic COVID-19 Infection With an Electrocardiogram: A Prospective Observational

Demilade Adedinsewo1, Jennifer Dugan2, Patrick W Johnson3

  • 1Department of Cardiovascular Medicine, Mayo Clinic, Jacksonville, FL.

Mayo Clinic Proceedings. Digital Health
|April 10, 2025
PubMed
Summary

A point-of-care AI-ECG device was ineffective in detecting asymptomatic SARS-CoV-2 infection. This highlights the need for rigorous prospective testing and similar data when developing AI-ECG tools for disease detection.

More Related Videos

Patient Directed Recording of a Bipolar Three-Lead Electrocardiogram using a Smartwatch with ECG Function
05:03

Patient Directed Recording of a Bipolar Three-Lead Electrocardiogram using a Smartwatch with ECG Function

Published on: December 11, 2019

8.5K
Signal Acquisition, Score Interpretation, and Economics of a Non-Invasive Point-of-Care Test for Coronary Artery Disease
06:16

Signal Acquisition, Score Interpretation, and Economics of a Non-Invasive Point-of-Care Test for Coronary Artery Disease

Published on: August 9, 2024

323

Related Experiment Videos

Last Updated: May 15, 2025

A High-Throughput Multiplexed Screening for Type 1 Diabetes, Celiac Diseases, and COVID-19
06:46

A High-Throughput Multiplexed Screening for Type 1 Diabetes, Celiac Diseases, and COVID-19

Published on: July 5, 2022

2.7K
Patient Directed Recording of a Bipolar Three-Lead Electrocardiogram using a Smartwatch with ECG Function
05:03

Patient Directed Recording of a Bipolar Three-Lead Electrocardiogram using a Smartwatch with ECG Function

Published on: December 11, 2019

8.5K
Signal Acquisition, Score Interpretation, and Economics of a Non-Invasive Point-of-Care Test for Coronary Artery Disease
06:16

Signal Acquisition, Score Interpretation, and Economics of a Non-Invasive Point-of-Care Test for Coronary Artery Disease

Published on: August 9, 2024

323

Area of Science:

  • Artificial Intelligence in Medicine
  • Cardiology
  • Infectious Diseases

Background:

  • Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection poses a global health challenge.
  • Point-of-care (POC) diagnostic tools are crucial for rapid detection.
  • Artificial intelligence (AI) applied to electrocardiography (ECG) shows potential for disease identification.

Purpose of the Study:

  • To evaluate the efficacy of a neural network-powered POC AI-ECG device for identifying SARS-CoV-2 infection.
  • To assess the accuracy of a handheld, smartphone-compatible AI-ECG in detecting asymptomatic SARS-CoV-2.

Main Methods:

  • A prospective observational study enrolled 2827 patients between December 2020 and June 2021.
  • A modified deep learning model, trained on 12-lead ECG data, was adapted for POC AI-ECG.
  • The AI-ECG's ability to detect asymptomatic SARS-CoV-2 infection was analyzed.

Main Results:

  • The POC AI-ECG algorithm demonstrated ineffectiveness in detecting asymptomatic SARS-CoV-2 infection (AUC = 0.56).
  • The algorithm failed to reliably discriminate between ECGs of SARS-CoV-2 positive and negative participants.
  • Participant demographics included 48% female, 79% White, and 7% with prior COVID-19 infection.

Conclusions:

  • A POC AI-ECG tool was not reliable for identifying asymptomatic SARS-CoV-2 infection in adults.
  • Prospective testing with similar populations and data is essential for developing effective AI-ECG diagnostic tools.
  • The findings contrast with previous studies using 12-lead ECG data.