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

Electrocardiogram Fundamentals01:28

Electrocardiogram Fundamentals

470
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...
470

You might also read

Related Articles

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

Sort by
Same author

Electrocardiogram-derived respiratory rate: State-of-the-art and implications for remote cardiopulmonary monitoring.

NPJ digital medicine·2026
Same author

Influence of pericardium on ventricular mechanical interdependence in an isolated biventricular working pig heart model.

The Journal of physiology·2024
Same author

Origin of ventricular fibrillation triggers in a model of localized repolarization heterogeneity.

Heart rhythm·2024
Same author

A His bundle pacing protocol for suppressing ventricular arrhythmia maintenance and improving defibrillation efficacy.

Computer methods and programs in biomedicine·2024
Same author

Investigation into the importance of using natural PVCs and pathological models for potential-based ECGI validation.

Frontiers in physiology·2023
Same author

The circle of reentry: Characteristics of trigger-substrate interaction leading to sudden cardiac arrest.

Frontiers in cardiovascular medicine·2023

Related Experiment Video

Updated: May 20, 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

338

ECG electrode localization using 3D visual reconstruction.

Ayoub El Ghebouli1, Amaël Mombereau1, Michel Haïssaguerre1,2

  • 1University Bordeaux, Institut national de la sante et de la recherche medicale (INSERM), U-1045, IHU Liryc, Le Centre de Recherche Cardio-Thoracique de Bordeaux (CRCTB), Bordeaux, France.

Frontiers in Physiology
|March 27, 2025
PubMed
Summary
This summary is machine-generated.

AI methods accurately locate electrodes for body surface potential maps (BSPMs) using 3D or 2D cameras. This offers a practical, accurate alternative to traditional imaging for enhanced clinical electrophysiology.

Keywords:
2D camera3D cameraAIBSPMECG electrodes localization

More Related Videos

Recording Human Electrocorticographic ECoG Signals for Neuroscientific Research and Real-time Functional Cortical Mapping
13:32

Recording Human Electrocorticographic ECoG Signals for Neuroscientific Research and Real-time Functional Cortical Mapping

Published on: June 26, 2012

25.7K
Brain Source Imaging in Preclinical Rat Models of Focal Epilepsy using High-Resolution EEG Recordings
08:20

Brain Source Imaging in Preclinical Rat Models of Focal Epilepsy using High-Resolution EEG Recordings

Published on: June 6, 2015

15.2K

Related Experiment Videos

Last Updated: May 20, 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

338
Recording Human Electrocorticographic ECoG Signals for Neuroscientific Research and Real-time Functional Cortical Mapping
13:32

Recording Human Electrocorticographic ECoG Signals for Neuroscientific Research and Real-time Functional Cortical Mapping

Published on: June 26, 2012

25.7K
Brain Source Imaging in Preclinical Rat Models of Focal Epilepsy using High-Resolution EEG Recordings
08:20

Brain Source Imaging in Preclinical Rat Models of Focal Epilepsy using High-Resolution EEG Recordings

Published on: June 6, 2015

15.2K

Area of Science:

  • Biomedical Engineering
  • Medical Imaging
  • Electrophysiology

Background:

  • Body surface potential maps (BSPMs) offer advanced electrophysiological insights beyond standard ECG.
  • Accurate electrode localization is crucial for reliable BSPM generation.
  • Current localization methods can be complex or require specialized equipment.

Purpose of the Study:

  • To develop and validate AI-based methods for automatic electrode localization in BSPMs.
  • To compare the accuracy of a 3D Depth Sensing camera method with a 2D camera method.
  • To assess the clinical feasibility of these AI-driven localization techniques.

Main Methods:

  • Developed two AI algorithms for electrode detection: one rapid (3D DS camera) and one versatile (2D camera).
  • Validated both methods against CT scans and Electromagnetic Tracking Systems (ETS) using a phantom model.
  • Tested the methods on 7 healthy volunteers to determine real-world accuracy.

Main Results:

  • Both 3D DS and 2D camera methods achieved sub-2mm localization error on the phantom model.
  • Volunteer studies showed average 3D Euclidean distances between 2.45 ± 1.32 mm and 5.78 ± 3.09 mm.
  • The AI methods demonstrated comparable accuracy to established tracking systems.

Conclusions:

  • AI-powered electrode localization using 3D or 2D cameras is highly accurate for BSPMs.
  • These methods provide practical and potentially cost-effective alternatives to traditional imaging.
  • The findings may increase clinical adoption and utility of BSPMs in diagnosing cardiac conditions.