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Related Concept Videos

Electrocardiogram Fundamentals01:28

Electrocardiogram Fundamentals

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Introduction
An electrocardiogram (ECG) is a diagnostic tool for identifying cardiac conditions such as arrhythmias, conduction abnormalities, and myocardial ischemia.
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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.
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Electrophysiology of Normal Cardiac Rhythm01:19

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The normal cardiac rhythm is a synchronized electrical activity that facilitates the regular and coordinated contraction of the heart muscle. This process is essential for efficient blood circulation throughout the body. The fundamental elements involved in establishing and maintaining this rhythm include the unique electrical properties of cardiac muscle cells, the sinoatrial (SA) node's pacemaker function, the specialized conducting system, and the ionic mechanisms underlying each phase...
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Dysrhythmias II: Classification of Tachyarrhythmias01:28

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Tachyarrhythmias are a type of dysrhythmia where the heart rate exceeds 100 beats per minute. Here are some common types of tachyarrhythmias:Sinus TachycardiaSinus tachycardia originates from increased impulses from the sinus node, leading to an elevated heart rate. It is often triggered by stress, fever, or exercise.Patients may experience palpitations, a sensation of a racing heart, dizziness, and chest discomfort.Causes and Risk Factors: Common causes include physical exertion, emotional...
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Dysrhythmias III: Characteristics of Dysrhythmias01:29

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Dysrhythmias, also known as arrhythmias, are irregular heart rhythms that result from abnormal electrical activity in the heart, affecting its ability to circulate blood efficiently. Tachyarrhythmias, a subset of dysrhythmias, are characterized by abnormally fast heart rates exceeding 100 beats per minute. Here are some types of tachyarrhythmias with their distinct ECG features:Sinus Tachycardia:Sinus tachycardia presents a regular heart rhythm with an increased rate of 101-180 beats per...
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Pulse rhythm01:30

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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.
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Assessment of apical radial pulse01:25

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Apical-Radial (A-R) Pulse Assessment
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Related Experiment Video

Updated: Mar 27, 2026

High-Resolution Endocardial and Epicardial Optical Mapping in a Sheep Model of Stretch-Induced Atrial Fibrillation
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Spiral wave classification using normalized compression distance: Towards atrial tissue spatiotemporal

Celal Alagoz, Allon Guez, Andrew Cohen

    Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
    |January 7, 2016
    PubMed
    Summary

    This study introduces a new method to classify spiral wave behaviors during atrial fibrillation (Afib) using catheter recordings. Normalized Compressed Distance (NCD) shows superior performance for analyzing cardiac electrical activity.

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    Area of Science:

    • Computational electrophysiology
    • Cardiac electrophysiology modeling
    • Biomedical signal processing

    Background:

    • Atrial fibrillation (Afib) analysis requires understanding re-entrant electrical activation patterns.
    • Spiral waves are key to re-entry mechanisms in cardiac tissue.
    • Classifying spiral wave behavior is essential for diagnosing Afib.

    Purpose of the Study:

    • To develop and validate an automated method for classifying spiral wave behaviors during simulated Afib.
    • To compare the effectiveness of Normalized Compressed Distance (NCD) and Normalized FFT (NFFTD) for this classification task.
    • To assess the impact of catheter type, location, and recording configuration (monopolar/bipolar) on classification accuracy.

    Main Methods:

    • Simulated spiral wave behaviors (stable, meandering, breakup) using a cardiac electrical propagation model on a 2D grid.
    • Simulated intracardiac electrograms mimicking star-shaped and circular catheters.
    • Applied NCD and NFFTD techniques for classifying simulated activation patterns.

    Main Results:

    • NCD demonstrated superior classification performance compared to NFFTD.
    • Classification accuracy showed slight variations based on catheter position and type.
    • The proposed method provides theoretical validation for qualitative wavefront assessment.

    Conclusions:

    • Automated classification of spiral wave behavior using NCD is feasible from simulated catheter recordings.
    • This approach offers a potential non-invasive method for characterizing electrophysiological activity during Afib.
    • Findings suggest a qualitative assessment of wavefront patterns is possible without complex mapping.