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Related Concept Videos

Design Example: Resistive Touchscreen01:14

Design Example: Resistive Touchscreen

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A device engineer plays a crucial role in designing user interfaces for mobile devices. One such interface is the resistive touchscreen, which fundamentally consists of two metallic layers: a flexible upper layer and a rigid lower layer, separated by a narrow gap. The high resistance between these two layers is a key characteristic of this design.
When a user touches the screen, the two layers make contact at a specific point known as the touchpoint. This contact reduces the resistance between...
815

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An Application for Pairing with Wearable Devices to Monitor Personal Health Status
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A dynamic data source selection system for smartwatch platform.

Ebrahim Nemati, Konstantinos Sideris, Haik Kalantarian

    Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
    |March 9, 2017
    PubMed
    Summary
    This summary is machine-generated.

    This study introduces a new algorithm for elderly activity tracking, dynamically switching between smartwatches and smartphones. This approach enhances accuracy and extends battery life for continuous health monitoring.

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    Area of Science:

    • Biomedical Engineering
    • Gerontology
    • Computer Science

    Background:

    • Ambulatory activity tracking is crucial for monitoring the health and well-being of elderly individuals.
    • Existing methods often face challenges with accuracy and battery limitations, impacting long-term usability.
    • Contextual information has the potential to optimize data collection strategies.

    Purpose of the Study:

    • To propose a novel data source selection algorithm for ambulatory activity tracking in the elderly.
    • To improve the accuracy and battery efficiency of activity tracking systems.
    • To dynamically switch between data collection modules (smartwatch and smartphone) based on contextual information.

    Main Methods:

    • Development of a dynamic switching algorithm that leverages contextual information.
    • Integration of smartwatch and smartphone as data collection modules.
    • Evaluation of the algorithm's performance against a baseline using activity-dependent offloading decisions.

    Main Results:

    • The proposed algorithm significantly improves power consumption compared to the baseline.
    • Accuracy of activity tracking is enhanced by 5% over previous methods.
    • Extended operational duration by 7 hours due to improved power management.

    Conclusions:

    • Dynamic data source selection is an effective strategy for optimizing elderly activity tracking systems.
    • The algorithm offers a practical solution for improving both the accuracy and battery life of wearable health monitoring devices.
    • This approach supports more reliable and continuous remote health monitoring for the elderly.