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Using a Real-Time Locating System to Measure Walking Activity Associated with Wandering Behaviors Among Institutionalized Older Adults
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Predictive Walking-Age Health Analyzer.

Priyanka Mandal, Krishna Tank, Tapas Mondal

    IEEE Journal of Biomedical and Health Informatics
    |February 17, 2017
    PubMed
    Summary
    This summary is machine-generated.

    This study introduces a wearable health analyzer using walking patterns to identify disease risks. The system classifies individuals into distinct walking-age groups, aiding early disease detection and management.

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    Area of Science:

    • Biomedical Engineering
    • Gait Analysis
    • Wearable Health Technology

    Background:

    • Early disease identification and management are crucial for public health.
    • Wearable technology offers a non-invasive approach to continuous health monitoring.
    • Gait analysis can reveal subtle physiological changes indicative of health status.

    Purpose of the Study:

    • To develop a simple, low-power, wearable health analyzer for early disease identification.
    • To characterize and classify individuals into distinct walking-age groups based on gait patterns.
    • To assess the potential of gait analysis as an ambulatory screening tool.

    Main Methods:

    • Utilized inertial signals (accelerometer, gyroscope) from 74 healthy adults (18-60 years).
    • Employed improved complete ensemble empirical mode decomposition with adaptive noise (improved CEEMDAN) for feature extraction.
    • Analyzed features like speed, energy, turn ratio, and bipedal behavior during level walking and turns.

    Main Results:

    • Healthy gait exhibits natural bipedal asymmetry related to functional attributes and age.
    • Turn ratio proved a more reliable indicator for health issues and fall risk than straight-line walking.
    • Successfully classified individuals into two walking-age groups (18-45 and 46-60 years) based on gait patterns.

    Conclusions:

    • The proposed wearable walking analyzer is a simple, inexpensive, and effective ambulatory screening tool.
    • It can assist clinicians in identifying at-risk populations for early disease onset.
    • Gait analysis, particularly turning dynamics, provides valuable insights into functional health.