Development and Applications of Daily-use Fall Risk Assessment Device to Prevent Elderly People From Falling
NCT05693480 · Status: UNKNOWN · Phase: NA · Type: INTERVENTIONAL · Enrollment: 1300
Last updated 2023-02-08
Summary
This research attempts to develop an artificial intelligence (AI) enabled device for measuring the dynamic balance ability of older people with a sensor using an optical principle called Frustrated Total Internal Reflection. The AI-based algorithm embedded in the device performs the data analysis for balance ability assessment and falling risk prediction. As a critical part of the research, a large-scale user study is needed to test the validity of the device regarding the dynamic balance ability assessment and the accuracy of the falling risk prediction provided by the device. Also, we plan to study the factors influencing user engagement in this device through the questionnaire-based survey and interview.
Conditions
- Fall
- Balanced
Interventions
- DEVICE
-
Balance sensor
Participants will engage in the device test, clinical assessment tests, and related user experience surveys to uncover problems in the effectiveness, efficiency, and acceptance of the device prototype. The whole test will last six months, and the outcome will be assessed pre- and post-implementation for comparison and validation. The major testing criteria include the validity and reliability of the device, user experiences, and the accuracy of the device's fall prediction.
Sponsors & Collaborators
-
Aberdeen Kai-fong Welfare Association
collaborator OTHER -
Hong Kong Young Women's Christian Association
collaborator OTHER -
The University of Hong Kong
lead OTHER
Study Design
- Allocation
- NA
- Purpose
- PREVENTION
- Masking
- NONE
- Model
- SINGLE_GROUP
Eligibility
- Min Age
- 60 Years
- Max Age
- 80 Years
- Sex
- ALL
- Healthy Volunteers
- Yes
Timeline & Regulatory
- Start
- 2022-07-01
- Primary Completion
- 2024-06-30
- Completion
- 2024-10-30
Countries
- Hong Kong
Study Locations
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