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Arrhythmia is a condition characterized by an irregular heart rhythm, with ECG changes that differ based on its origin and nature. The types of arrhythmias discussed below include atrial, junctional, and ventricular arrhythmias.Atrial ArrhythmiasPremature Atrial Complexes (PACs): PACs are early atrial beats caused by stress, caffeine, alcohol, electrolyte imbalances, hypoxia, hyperthyroidism, or certain medications (e.g., bronchodilators and decongestants). The ECG shows early P waves with an...
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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.
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The electrical signals recorded on an electrocardiogram (ECG) occur before the mechanical processes of contraction and relaxation during the cardiac cycle.
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Cardiac action potentials are essential for proper heart function, enabling the rhythmic contractions needed for adequate blood circulation. Nodal cells and Purkinje fibers, specialized for electrical conduction, generate these action potentials.
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Introduction
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Bradyarrhythmias are cardiac rhythm disorders characterized by a slower-than-normal heart rate, typically defined as fewer than 60 beats per minute. Some of which are discussed here:Sinus BradycardiaSinus bradycardia presents a heart rate lower than 60 beats per minute, with a regular rhythm originating from the SA node. The ECG typically shows normal P waves preceding each QRS complex, a normal PR interval (0.12 to 0.20 seconds), and a normal QRS duration (0.06 to 0.10 seconds).First-Degree AV...
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Related Experiment Video

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High-Resolution Endocardial and Epicardial Optical Mapping in a Sheep Model of Stretch-Induced Atrial Fibrillation
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Bipolar Intracardiac Electrogram Active Interval Extraction During Atrial Fibrillation.

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    Summary
    This summary is machine-generated.

    We developed new methods to accurately identify active intervals (AIs) in intracardiac electrograms (IEGMs) during atrial fibrillation (AF). These techniques enable real-time automated analysis of complex arrhythmias.

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    Area of Science:

    • Cardiology
    • Biomedical Engineering
    • Signal Processing

    Background:

    • Atrial fibrillation (AF) is a complex arrhythmia requiring precise analysis of intracardiac electrograms (IEGMs).
    • Identifying active intervals (AIs) within IEGMs is crucial for understanding arrhythmia mechanisms and guiding treatment.
    • Current methods for AI detection may lack accuracy or real-time applicability.

    Purpose of the Study:

    • To introduce novel methods for accurate identification of active intervals (AIs) in intracardiac electrograms (IEGMs).
    • To address the challenge of analyzing complex arrhythmias like atrial fibrillation (AF) through precise AI detection.
    • To enable real-time automated analysis of IEGMs during AF.

    Main Methods:

    • Formulated AI extraction as a sequence of hypothesis tests comparing segment variances.
    • Proposed modified general-likelihood ratio (MGLR) and separating-function-estimation tests.
    • Derived five test statistics (TSs) for AI detection via threshold crossing.

    Main Results:

    • Achieved high similarity between proposed methods and manual annotation (MA).
    • Demonstrated true positive rates of 97.8% and false positive rates of 1.4% for an MGLR-based method.
    • Reported mean absolute errors of 8.7 ms for AI onset, 13 ms for AI end, and 4.2 ms for mean cycle length.

    Conclusions:

    • The proposed methods accurately identify the onset and duration of AIs in IEGMs during AF.
    • These novel techniques offer a reliable tool for real-time automated analysis of AF.
    • The findings contribute to improved understanding and management of complex cardiac arrhythmias.