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Related Concept Videos

Electrocardiogram01:29

Electrocardiogram

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 the T...
Electrocardiogram Fundamentals01:28

Electrocardiogram Fundamentals

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

Correlation between ECG and Cardiac Cycle

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...
Imaging Studies for Cardiovascular System I:Echocardiography01:17

Imaging Studies for Cardiovascular System I:Echocardiography

Cardiac imaging studies encompass a wide range of noninvasive and minimally invasive techniques designed to visualize the heart's structure and function in detail. One such technique is echocardiography, which uses high-frequency ultrasound waves to produce detailed images of the heart, known as echocardiograms.
Indications: Echocardiography is utilized to diagnose heart failure, valve disorders, and myocardial infarction. It also assesses cardiac structures' size, shape, and motion, evaluates...
Pulse rhythm01:30

Pulse rhythm

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 muscle...
Imaging Studies for Cardiovascular System II:Types of Echocardiography01:20

Imaging Studies for Cardiovascular System II:Types of Echocardiography

Echocardiography plays a role in assessing cardiac health and detecting heart conditions, with various types providing critical insights for diagnosis and treatment.
Types of Echocardiography
Transthoracic Echocardiography (TTE)
TTE is the most common type of echocardiogram which involves placing a transducer on the patient's chest, emitting sound waves to create heart images. TTE is invaluable for evaluating the heart's size, structure, and motion, making it particularly useful for diagnosing...

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Related Experiment Videos

Leveraging 3D Heart Visualisation and Data Balancing Techniques for ECG Classification.

Kahina Amara1, Oussama Kerdjidj1, Mohamed Amine Guerroudji1

  • 1Centre for Development of Advanced Technologies, Algiers 16081, Algeria.

Bioengineering (Basel, Switzerland)
|May 27, 2026
PubMed
Summary
This summary is machine-generated.

This study introduces a deep learning pipeline for automated arrhythmia classification from electrocardiograms (ECG). Novel 3D visualizations enhance diagnostic insight and anatomical localization of cardiac abnormalities.

Keywords:
3D visualisationarrhythmiabalancing techniquesclassificationdeep learningimbalanced dataset

Related Experiment Videos

Area of Science:

  • Cardiology
  • Medical Imaging
  • Artificial Intelligence

Background:

  • Cardiovascular diseases are a major global health concern.
  • Electrocardiogram (ECG) analysis is crucial but can be time-consuming and error-prone.
  • Automated methods are needed to improve accuracy and efficiency in cardiac abnormality diagnosis.

Purpose of the Study:

  • To develop a deep learning pipeline for automated arrhythmia classification using ECG data.
  • To address challenges posed by imbalanced datasets in cardiac analysis.
  • To introduce a 3D visualization framework for enhanced diagnostic insight and anatomical localization.

Main Methods:

  • A comprehensive deep learning pipeline was designed for automated arrhythmia classification.
  • Specific data balancing strategies were implemented to handle imbalanced datasets.
  • A novel 3D visualization framework was developed for interactive anatomical rendering.

Main Results:

  • The proposed data balancing techniques significantly improved classification performance.
  • The automated system achieved competitive or superior results compared to existing methods.
  • 3D visualizations provided precise anatomical localization of arrhythmia substrates.

Conclusions:

  • The deep learning pipeline offers a promising approach for accurate automated arrhythmia classification.
  • The 3D visualization tool enhances clinical diagnosis and medical education.
  • Further inter-patient cross-validation is recommended to establish generalizability.