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Ion Channels

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The movement of ions like sodium, potassium, and calcium into and out of the cell is essential to maintain the electrochemical gradient in living cells. The ion channels—a class of membrane transport proteins—help maintain this ionic gradient for the smooth functioning of physiological activities such as maintaining cell size and volume, conducting nerve impulses, and gas and nutrient exchange.
Ion channels are specialized integral membrane proteins on the plasma membrane that allow...
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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.
Components of the Electrocardiogram
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Correlation between ECG and Cardiac Cycle01:25

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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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ECG Interpretation of Arrhythmias I: Sinus Arrhythmias01:16

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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.
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Sinus Node Arrhythmias
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Most organisms use photoreceptors to sense and respond to light. Examples of photoreceptors include bacteriorhodopsins and bacteriophytochromes in some bacteria, phytochromes in plants, and rhodopsins in the photoreceptor cells of the vertebral retina. The light-sensitive property of these receptors is because of the bound chromophores, such as bilin in the phytochromes and retinal in the rhodopsins.
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ECG Interpretation of Arrhythmias II: Atrial, Junctional and Ventricular Arrhythmias01:25

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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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Bacterial Detection & Identification Using Electrochemical Sensors
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Improving the QRS detection for one-channel ECG sensor.

Ervin Domazet, Marjan Gusev

    Technology and Health Care : Official Journal of the European Society for Engineering and Medicine
    |April 30, 2019
    PubMed
    Summary

    A new electrocardiogram (ECG) beat detector achieves 99.90% accuracy for QRS complex detection. This high-performance algorithm is optimized for wearable sensors, outperforming existing methods on standard ECG datasets.

    Keywords:
    QRS detectionbeat detectorelectrocardiogramoptimizationresamplerescalewearable sensors

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    Area of Science:

    • Biomedical Engineering
    • Signal Processing
    • Cardiology

    Background:

    • Wearable electrocardiogram (ECG) sensors require efficient and accurate QRS complex detection.
    • Existing algorithms may not be optimal for low-power, single-channel devices with limited sampling rates.
    • Robust QRS detection is crucial for remote patient monitoring and arrhythmia diagnosis.

    Purpose of the Study:

    • To develop a high-quality industrial QRS detection algorithm for small, wearable ECG sensors.
    • To optimize algorithm parameters and rules for enhanced accuracy and reliability.
    • To evaluate the performance of the developed algorithm against established benchmarks.

    Main Methods:

    • Analysis of multiple QRS detection algorithms.
    • Development of several hundred rules to address QRS detection challenges.
    • Optimization of threshold values for key algorithm parameters.
    • Testing on rescaled and resampled MIT-BIH Arrhythmia ECG database.

    Main Results:

    • Achieved 99.90% QRS sensitivity and 99.90% QRS positive predictive rate.
    • The developed algorithm outperformed existing methods on original, higher-sampling-rate ECG data.
    • The solution is specifically tailored for a 125 Hz sampling rate and 10-bit analog-to-digital conversion.

    Conclusions:

    • A novel QRS detection algorithm provides superior performance for wearable ECG devices.
    • The algorithm demonstrates high accuracy and robustness, suitable for industrial applications.
    • This advancement can improve the reliability of arrhythmia detection in portable healthcare solutions.