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Mechanism of Cardiac Arrhythmias01:28

Mechanism of Cardiac Arrhythmias

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Arrhythmias are irregular heart rhythms occurring when the heart's electrical impulses become abnormal. These disturbances can lead to various symptoms, depending on their severity and the underlying cause. Some common factors contributing to arrhythmias include hypoxia, ischemia, electrolyte imbalances, excessive catecholamine exposure, drug toxicity, and muscle overstretching. Arrhythmias can be classified into two main types based on the rate and site of origin of abnormal heart rhythms.
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Arrhythmias are disturbances in the heart's rhythm that lead to abnormal heartbeats. These irregularities can originate from different parts of the heart and are classified based on their origin and nature.
Types of Arrhythmias
Sinus Node Arrhythmias
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Real-time reverse transcription-polymerase chain reaction, or Real-time RT-PCR, is an analytical tool used to determine the expression level of target genes. The method involves converting mRNA to complementary DNA with the help of an enzyme known as reverse transcriptase, followed by the PCR amplification of the cDNA. These two processes can be performed simultaneously in a single tube or separately as a two-step reaction.
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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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Forces play a crucial role in the study of physics and engineering. They are essential in describing the motion, behavior, and equilibrium of objects in the physical world. Forces can be classified based on their origin, type, and direction of action.
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Real-Time Cardiac Arrhythmia Classification Using Memristor Neuromorphic Computing System.

Amr M Hassan, Aya F Khalaf, Khaled S Sayed

    Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
    |November 17, 2018
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    Summary
    This summary is machine-generated.

    This study presents a novel real-time cardiac arrhythmia classification system using memristor-based neuromorphic computing. The system achieves high accuracy and fast testing times, offering a promising advancement in life-saving arrhythmia detection.

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    Area of Science:

    • Biomedical Engineering
    • Computer Science
    • Materials Science

    Background:

    • Cardiac arrhythmia is a leading global cause of mortality, necessitating advanced detection methods.
    • Existing techniques face challenges in real-time processing, power efficiency, and accuracy.
    • Emerging technologies like memristors offer potential for improved diagnostic tools.

    Purpose of the Study:

    • To introduce a novel real-time cardiac arrhythmia classification system.
    • To leverage memristor-based neuromorphic computing for enhanced beat type classification.
    • To evaluate the system's performance against existing methods.

    Main Methods:

    • Development of a real-time cardiac arrhythmia classification system utilizing memristor neuromorphic computing.
    • Implementation of a system capable of classifying 5 different cardiac beat types.
    • Experimental validation of the proposed system's accuracy and processing speed.

    Main Results:

    • The proposed system achieved an average accuracy of 96.17% for cardiac arrhythmia classification.
    • The system demonstrated an average testing time of 34 ms per beat.
    • Comparative analysis indicated superior performance over existing methods in accuracy and testing time.

    Conclusions:

    • Memristor neuromorphic computing offers an effective platform for real-time cardiac arrhythmia detection.
    • The developed system provides a significant improvement in accuracy and processing speed.
    • This technology holds promise for improving patient outcomes through efficient arrhythmia diagnosis.