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Related Concept Videos

Electrocardiogram01:29

Electrocardiogram

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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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Electrocardiogram Fundamentals01:28

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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
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Dysrhythmias V: Evaluating Dysrhythmias01:30

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Dysrhythmias, also known as arrhythmias, are disturbances in the heart's rhythm that range from benign to life-threatening. A thorough evaluation is crucial for appropriate management and involves a comprehensive medical history, physical examination, and various diagnostic tests.Medical HistorySymptoms: Collect detailed information on palpitations, dizziness, syncope, chest pain, and fatigue. Note their onset, frequency, and triggers.Previous Cardiac Issues: Document any history of heart...
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ECG Interpretation of Rhythms01:24

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An electrocardiogram (ECG)graphically represents the heart's electrical activity on ECG paper or a monitor.
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High-Throughput Analysis of Optical Mapping Data Using ElectroMap
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Comparative evaluation of methodologies for T-wave alternans mapping in electrograms.

Michele Orini, Ben Hanson, Violeta Monasterio

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    Accurate detection of T-wave alternans (TWA) in electrograms (EGM) is crucial for predicting arrhythmias. The Laplacian Likelihood Ratio (LLR) method demonstrates superior robustness in noisy conditions compared to other TWA detection techniques.

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    Area of Science:

    • Cardiovascular Electrophysiology
    • Biomedical Signal Processing

    Background:

    • Electrograms (EGM) from the heart surface are increasingly accessible.
    • T-wave alternans (TWA) precedes ventricular arrhythmias, indicating vulnerability.

    Purpose of the Study:

    • To compare the accuracy of four time-varying TWA estimation methods using human epicardial EGM simulations.
    • To evaluate method performance under various noise conditions, including wide-band noise, respiration, and impulse artifacts.

    Main Methods:

    • Simulation study using in vivo human epicardial EGM data.
    • Comparison of Spectral Method (SM), modified moving average, Laplacian Likelihood Ratio (LLR), and a novel time-frequency distribution method.
    • Analysis of TWA detection accuracy under simulated noise and artifact conditions.

    Main Results:

    • Accurate TWA detection is feasible when wide-band noise is low (noise std. dev. ≤ 10x TWA magnitude).
    • Respiration significantly impacts EGM-TWA analysis; impulse noise severely degrades most methods except LLR.
    • LLR exhibited the highest robustness, offering better detection rates in noisy environments.

    Conclusions:

    • The Laplacian Likelihood Ratio (LLR) method is the most robust for TWA detection in electrograms, especially under noisy conditions.
    • TWA detection accuracy is maintained even with imprecise T-wave localization if depolarization time is used as a fiducial point.
    • In vivo human epicardial mapping revealed heterogeneous spatio-temporal distribution of EGM-TWA.