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

3.3K
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...
3.3K
Correlation between ECG and Cardiac Cycle01:25

Correlation between ECG and Cardiac Cycle

8.7K
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...
8.7K
Electrocardiogram Fundamentals01:28

Electrocardiogram Fundamentals

903
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...
903

You might also read

Related Articles

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

Sort by
Same author

Standardized processing of explanted hearts after stereotactic arrhythmia radiotherapy (Bio-STAR): a STOPSTORM framework and first human findings.

European heart journal open·2026
Same author

Cluster analysis: an overview of traditional and novel approaches for health researchers.

European journal of cardiovascular nursing·2026
Same author

Multilevel Atrioventricular Block After Cardiac Surgery.

JACC. Case reports·2026
Same author

Incidence and type of recurrent ventricular arrhythmia in patients with arrhythmic mitral valve prolapse and implantable cardioverter defibrillator for secondary prevention.

Europace : European pacing, arrhythmias, and cardiac electrophysiology : journal of the working groups on cardiac pacing, arrhythmias, and cardiac cellular electrophysiology of the European Society of Cardiology·2026
Same author

To the editor-The time has come for a prospective randomized trial to evaluate the safety of class IC drugs in patients with coronary artery disease.

Heart rhythm·2026
Same author

Prevalence of Early Rheumatic Heart Disease Among Asymptomatic Students in Underserved Communities in Ethiopia: Cross-Sectional Observational Study.

JMIR public health and surveillance·2026
Same journal

Correction: A method for supervoxel-wise association studies of age and other non-imaging variables from coronary computed tomography angiograms.

Scientific reports·2026
Same journal

Poly(bromophenol blue)/CoSn(OH)<sub>6</sub> cubic particles modified pencil graphite electrode for electrochemical determination of diphenhydramine.

Scientific reports·2026
Same journal

Dietary Chlorella, Spirulina, and acidifier modulate jejunal cytokine-related gene expression in broiler chickens.

Scientific reports·2026
Same journal

Perceived physical activity barriers in university students: associations with fatigue and eating behaviours.

Scientific reports·2026
Same journal

Refuge limitation structures habitat use in agricultural landscapes: evidence from Sunda pangolins.

Scientific reports·2026
Same journal

Lightweight stateless transaction verification with outsourced witness updates for UTXO blockchains.

Scientific reports·2026
See all related articles

Related Experiment Video

Updated: Sep 25, 2025

Analyzing Long-Term Electrocardiography Recordings to Detect Arrhythmias in Mice
06:07

Analyzing Long-Term Electrocardiography Recordings to Detect Arrhythmias in Mice

Published on: May 23, 2021

3.9K

A machine learning algorithm for electrocardiographic fQRS quantification validated on multi-center data.

Amalia Villa1, Bert Vandenberk2,3, Tuomas Kenttä4

  • 1Department of Electrical Engineering (ESAT), STADIUS Center for Dynamical Systems, Signal Processing and Data Analytics, KU Leuven, Leuven, Belgium. amalia.villagomez@kuleuven.be.

Scientific Reports
|April 27, 2022
PubMed
Summary
This summary is machine-generated.

Fragmented QRS (fQRS) on ECG indicates heart conduction issues and higher mortality risk. This study introduces an automated method for objective fQRS detection and quantification, improving clinical risk assessment.

More Related Videos

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

2.6K
Estimating Bilateral Atrial Function by Cardiovascular Magnetic Resonance Feature Tracking in Patients with Paroxysmal Atrial Fibrillation
08:10

Estimating Bilateral Atrial Function by Cardiovascular Magnetic Resonance Feature Tracking in Patients with Paroxysmal Atrial Fibrillation

Published on: July 20, 2022

1.8K

Related Experiment Videos

Last Updated: Sep 25, 2025

Analyzing Long-Term Electrocardiography Recordings to Detect Arrhythmias in Mice
06:07

Analyzing Long-Term Electrocardiography Recordings to Detect Arrhythmias in Mice

Published on: May 23, 2021

3.9K
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

2.6K
Estimating Bilateral Atrial Function by Cardiovascular Magnetic Resonance Feature Tracking in Patients with Paroxysmal Atrial Fibrillation
08:10

Estimating Bilateral Atrial Function by Cardiovascular Magnetic Resonance Feature Tracking in Patients with Paroxysmal Atrial Fibrillation

Published on: July 20, 2022

1.8K

Area of Science:

  • Cardiology
  • Biomedical Engineering
  • Signal Processing

Background:

  • Fragmented QRS (fQRS) is an ECG marker for myocardial conduction abnormalities, linked to increased mortality and arrhythmia risk in cardiovascular patients.
  • Current visual analysis of fQRS suffers from observer variability and inconsistent definitions, hindering clinical application.
  • Objective quantification of fQRS is crucial for improved risk stratification in patients with cardiovascular disease.

Purpose of the Study:

  • To develop and validate an automated method for detecting and quantifying fragmented QRS (fQRS) on electrocardiograms (ECGs).
  • To overcome the limitations of subjective visual analysis and provide objective fQRS assessment for enhanced clinical risk stratification.

Main Methods:

  • A novel QRS complex segmentation strategy integrating multi-lead ECG information and automatic exclusion of abnormal beats.
  • Feature extraction using variational mode decomposition (VMD), phase-rectified signal averaging (PRSA), and ECG baseline crossings.
  • Training a Support Vector Machine (SVM) classifier on multi-center data, combining various fQRS criteria, and validating against expert annotations.

Main Results:

  • The automated method achieved Kappa scores of 0.68 and 0.44 when compared to visual fQRS annotations on two independent datasets.
  • The algorithm demonstrated effectiveness in both regular sinus rhythm and irregular rhythms, such as atrial fibrillation.
  • The developed approach provides objective assessment and quantification of fQRS, showing potential for clinical utility.

Conclusions:

  • The proposed automated method offers an objective and reliable approach for fQRS detection and quantification, addressing limitations of current visual analysis.
  • This algorithm has the potential to significantly improve cardiovascular disease risk stratification by providing precise fQRS assessment.
  • The study paves the way for the clinical integration of automated fQRS analysis, enhancing patient care and outcomes.