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Implementing and Evaluating the Timed Up and Go Test Automation Using Smartphones and Smartwatches.

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    This study introduces a mobile health system to automate the Timed Up and Go (TUG) test using smartphones or smartwatches. This technology enables self-administered mobility assessments, improving accessibility and efficiency for patients and healthcare providers.

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    Area of Science:

    • Biomedical Engineering
    • Digital Health
    • Rehabilitation Technology

    Background:

    • Physical performance tests, like the Timed Up and Go (TUG) test, are crucial for assessing mobility but are often resource-intensive and require expert supervision.
    • Objective measurements in physical tests are amenable to technological automation, enabling self-administration, increased frequency, and remote monitoring.
    • The TUG test, a standard mobility assessment, presents an opportunity for automation using wearable sensors.

    Purpose of the Study:

    • To develop and evaluate a mobile health (mHealth) system for automating the Timed Up and Go (TUG) test.
    • To enable self-administered TUG testing using readily available devices like smartphones and smartwatches.
    • To compare the accuracy, reliability, and battery consumption of smartphone-based versus smartwatch-based TUG test automation.

    Main Methods:

    • Development of an mHealth system utilizing inertial sensor data from smartphones or smartwatches paired with a smartphone.
    • Real-time processing of sensor data on the smartphone for activity detection and TUG test result calculation.
    • Evaluation of the system's performance against a reference method, assessing accuracy, reliability (Intraclass Correlation Coefficient), and battery usage, with Bland-Altman analysis.

    Main Results:

    • The mHealth system successfully automated the TUG test using both smartphone and smartwatch configurations.
    • Excellent agreement (Bland-Altman analysis) and reliability (Intraclass Correlation Coefficient) were achieved when compared to a reference method.
    • The smartwatch-based system demonstrated superior performance compared to the smartphone-based system in terms of accuracy, reliability, and potentially battery efficiency.

    Conclusions:

    • Automated TUG testing via mHealth systems is feasible, offering a scalable solution for mobility assessment.
    • Wearable technology, particularly smartwatches, holds significant promise for accurate and reliable self-administered physical performance testing.
    • This technology can reduce healthcare resource burden and empower individuals with more frequent and accessible mobility monitoring.