AIoT-based smart exercise system for older adults
Official title: Development of a Precision Exercise System for Older Adults and People With Stroke Using Deep Learning and Facial Action Units
Run by I-Shou University · NCT07779824 · Data updated 2026-11-12
This study tests an AIoT-powered exercise system to see if it improves fitness and functional performance in adults over 50 who are generally healthy.
Quick facts
| Study type | Interventional |
|---|---|
| Ages | 50 Years and up |
| Sex | All |
| Enrollment | 200 (estimated) |
| Sponsor | I-Shou University Academic / other |
| Locations | 1 site (Kaohsiung City) |
| Status | Recruiting |
| Started | February 20, 2026 |
| Main results expected | July 31, 2028 |
| Study ends | July 31, 2028 |
| Registry record updated | August 26, 2026 |
| Trial ID | NCT07779824 on ClinicalTrials.gov |
Is this trial a fit for you?
✓Likely a good fit
Adults over 50 without significant limb issues, cardiovascular disease, balance problems in the past year, or cognitive deficits who are able to participate in twice-weekly aerobic exercise.
✕Probably not a fit
Individuals with cardiovascular disease, recent balance problems, significant joint issues, or cognitive impairment may not benefit from this program.
A plain-English reading of the study's rules. Only the study team can confirm whether you qualify.
What this trial studies
Participants will complete a 12-week program using an AIoT-based cycle ergometer, with assessments at baseline and after 12 weeks. Continuous collection of data such as workload, heart rate, oxygen use, perceived exertion, and facial expressions will accompany the workouts. A safety check with blood pressure is performed before each session, and a user experience questionnaire is given at the end. The study will provide insights into how real-time data and AI-enabled feedback may support senior physical fitness training.
Why it matters
Potential benefit: If successful, the approach could help older adults improve physical fitness and daily function with guided, data-driven exercise.
How similar studies have gone: Previous work with AI-enabled exercise systems in older adults has shown feasibility, with some improvements in fitness measures, though results vary by protocol.
Who can join: the full rules
Show full inclusion / exclusion criteria
Inclusion Criteria: * Adult over 50 years old * No significant limb disability or joint deformation * No history of cardiovascular disease * Never lost balance due to dizziness in the past 12 months Exclusion Criteria: * Limb disability or joint deformation * History of cardiovascular disease * Lost balance due to dizziness in the past 12 months * Cognitive deficits
Where it's running
-
I-Shou University
Kaohsiung City, Taiwan Recruiting
Study contacts
- Study coordinator: Chih-Chun Lin
- Email: chihchunlin@isu.edu.tw
- Phone: +886-76151100 Ext. 7566
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How to take part
- Review the eligibility criteria above with your treating physician.
- Check the official listing on ClinicalTrials.gov for the latest contact details and recruitment status.
- Contact the study coordinator or principal investigator to ask for pre-screening. Pre-screening is free and never obligates you to enroll.