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Related Concept Videos

Pulse rhythm01:30

Pulse rhythm

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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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Holter monitoring is a continuous electrocardiography (ECG) recording that tracks the heart's electrical activity over an extended period, generally 24 to 48 hours. This noninvasive diagnostic tool detects irregular heart rhythms that may not be captured during a standard ECG performed in a clinical setting.DeviceThe Holter monitor is a portable, small device connected to several electrodes on the patient's chest. These electrodes detect the heart's electrical signals and transmit them to the...
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Related Experiment Video

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Methodology for Establishing a Community-Wide Life Laboratory for Capturing Unobtrusive and Continuous Remote Activity and Health Data
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Biovitals™: A Personalized Multivariate Physiology Analytics Using Continuous Mobile Biosensors.

Jin Chen, Minghao Yan, Robin Low Chin Howe

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    This study introduces personalized multivariate physiology analytics for remote patient monitoring, improving chronic disease management and reducing false alarms. Wearable biosensors detect early health changes, enhancing patient safety and quality of life.

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    Area of Science:

    • Biomedical Engineering
    • Health Informatics
    • Physiological Monitoring

    Background:

    • Chronic diseases affect over 50% of the global population, incurring a $47 trillion economic burden.
    • Healthcare is shifting towards remote patient management to improve safety and quality of life.
    • Current remote monitoring analytics using population thresholds yield poor outcomes and high false alarm rates.

    Purpose of the Study:

    • To present a novel personalized multivariate physiology analytics for ambulatory remote patient monitoring.
    • To address the limitations of current population-level monitoring systems.

    Main Methods:

    • Leveraging low-cost wearable biosensors for continuous physiological data collection.
    • Developing personalized analytics to detect subtle, precursor changes in individual physiology.
    • Utilizing perturbation testing and clinical trials for verification and validation.

    Main Results:

    • Demonstrated the capability of personalized analytics to detect early signs of health deterioration.
    • Showcased reduced false alarm burden compared to population-level threshold methods.
    • Verified and validated the novel analytics through rigorous testing.

    Conclusions:

    • Personalized multivariate physiology analytics offers a promising approach for effective remote patient monitoring.
    • This technology can significantly improve patient outcomes and healthcare efficiency in managing chronic diseases.
    • The system enhances patient safety by enabling early intervention through subtle physiological change detection.