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Related Concept Videos

Electrocardiogram Fundamentals01:28

Electrocardiogram Fundamentals

559
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...
559
Electrocardiogram01:29

Electrocardiogram

2.3K
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...
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Updated: Jun 22, 2025

Real-Time Cardiac Mapping with a Noninvasive Imageless Electrocardiographic Imaging System
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A Singular-Value-Based Map to Highlight Abnormal Regions Associated With Atrial Fibrillation Using High-Resolution

Hanie Moghaddasi, Richard C Hendriks, Borbala Hunyadi

    IEEE Transactions on Bio-Medical Engineering
    |June 28, 2024
    PubMed
    Summary

    New singular value analysis of atrial fibrillation (AF) reveals distinct waveform variations. This method enhances detection and evaluation of AF, potentially identifying problematic tissue regions without complex calculations.

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    Area of Science:

    • Cardiovascular Electrophysiology
    • Biomedical Signal Processing
    • Medical Diagnostics

    Background:

    • Atrial fibrillation (AF) severity is typically assessed using metrics like conduction block (CB) and continuous conduction delay and block (cCDCB) from epicardial electrograms.
    • Existing methods focus on conduction velocity and wavefront propagation, overlooking crucial information from atrial action potential morphology.
    • A need exists for novel analytical approaches to capture complementary electrophysiological properties for improved AF assessment.

    Purpose of the Study:

    • To derive and evaluate new features based on atrial potential waveform morphology for detecting variations associated with atrial fibrillation.
    • To explore the utility of singular value decomposition of epicardial measurements for characterizing AF.
    • To investigate the potential of this non-parametric method for identifying electropathological regions.

    Main Methods:

    • Utilized singular value decomposition (SVD) on epicardial measurement matrices to analyze spatial variations in atrial potential morphology during a single beat.
    • Developed a non-parametric method requiring minimal preprocessing.
    • Conducted simultaneous measurements of electrograms (EGMs) and multi-lead electrocardiograms (ECGs) to compare invasive and non-invasive data.

    Main Results:

    • Normalized singular values were significantly higher during AF compared to sinus rhythm (SR).
    • The difference in normalized singular values between AF and SR was more pronounced in non-invasive ECG data than in EGM data under favorable electrode placement.
    • Singular value maps effectively highlighted areas susceptible to conduction fractionation and block.

    Conclusions:

    • Singular value-based features derived from atrial potential morphology offer a valuable tool for detecting and evaluating atrial fibrillation.
    • The proposed method provides a promising approach for identifying electropathological regions without the need for local activation time estimation.
    • This technique enhances the understanding of AF pathophysiology by incorporating waveform morphology.