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Using Consumer-grade Wearable Devices for Fall Risk Evaluation and Alerts
Sponsor: University of Michigan
Summary
Creation and use of a smartphone application for older adults to assess the participants' risk of fall. Phase 1: Compare the accuracy and validity of accelerometer and gyroscopic data from a smartphone and gold-standard, wearable sensors gathered during balance and gait activities. Phase 2: Develop a model that integrates wearable sensor data and individual characteristics, such as age, medical conditions, exercises, previous falls, fear of falls, along with gait and balance outcome measurements, to evaluate fall risk in older adults. Phase 3: Integrate the computational model in the design of a mobile app for wearable devices for older adults to self-administer fall risk assessments and provide individualized risk of fall information.
Key Details
Gender
All
Age Range
65 Years - Any
Study Type
OBSERVATIONAL
Enrollment
100
Start Date
2024-07-29
Completion Date
2026-12-31
Last Updated
2025-08-06
Healthy Volunteers
Yes
Conditions
Interventions
risk of fall
Gather information that will assist in determining risk of fall. The researchers will ask the subjects to perform several motor tests and study-related questionnaires.
Locations (1)
University of Michigan-Flint
Flint, Michigan, United States