Using Consumer-grade Wearable Devices for Fall Risk Evaluation and Alerts

Part of paid clinical trials in Flint, Michigan.

Sponsor
University of Michigan
Study ID
NCT06508892
Status
Recruiting
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Conditions

  • Mass Screening

Eligibility Criteria

Sex
ALL
Age
65 Years - N/A
Healthy Volunteers
Accepted

Interventions

  • risk of fall — BEHAVIORAL
    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.

Study Details

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 Dates

Start date
Jul 29, 2024
Status verified
Aug 2025
Primary completion
Dec 31, 2026
Completion
Dec 31, 2026

Study Design

Enrollment
100 participants (estimated)

Arms

  • Arm: Comparison of acceleration and 3D rotation during balance and movement
    Can consumer-grade sensors used in mobile phones provide an accurate and valid measure of balance and gait when compared to gold standard research-grade sensors? A computational model for risk of fall will be developed.

Primary Outcome Measure

3D acceleration [ Time Frame: 60 seconds to 6 minutes ]

Central Contacts

Locations (1)

FacilityCityStateZIPSite coordinators
University of Michigan-FlintFlintMichigan48502
Nathan Miller, Ph.D.
[email protected]
810-762-3234
Cathy A Larson, Ph.D.
[email protected]
8107623373
Linda Zhu, Ph.D. (SUB_INVESTIGATOR)
Jennifer Liao, Ph.D. (PRINCIPAL_INVESTIGATOR)
Charlotte Tang, Ph.D. (SUB_INVESTIGATOR)

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By research site
University of Michigan-Flint· Flint, MI

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