Dual-track Residential Exercise With AI and Monitoring for Sleep
NCT07513584 · Status: NOT_YET_RECRUITING · Phase: NA · Type: INTERVENTIONAL · Enrollment: 60
Last updated 2026-04-07
Summary
As societies rapidly transition toward aging demographics, sleep issues among community-dwelling older adults have emerged as a critical concern affecting healthy aging and independent living. Current single-track exercise intervention models are often difficult to implement due to suboptimal adherence. Therefore, this study aims to utilize artificial intelligence technology combined with a dual-track residential exercise mode to improve sleep quality, thereby enhancing the self-care and independent living abilities of the elderly
Conditions
- Chronic Insomnia Characterized
- Difficulty Falling Asleep
- Difficulty Maintaining Sleep
- Healthy Aging and Independent Living
Interventions
- DEVICE
-
Fit Mirror-Guided Home-Based Exercise Program
The DREAMS Study evaluates an AI-driven, home-based, dual-track exercise intervention for community-dwelling older adults (≥ 60) with chronic insomnia. Integrating FitMirror skeletal recognition for real-time guidance and ActiGraph wearable monitoring for continuous data collection, the system creates a closed-loop feedback mechanism to optimize sleep health. The intervention is tailored to insomnia phenotypes: daytime HIIT or resistance training is prescribed to enhance sleep drive (targeting sleep-onset difficulties), while nighttime yoga or Pilates targets reduced hyperarousal (targeting sleep-maintenance difficulties). Using a quasi-experimental design, the study measures improvements in multi-dimensional sleep health and functional fitness at baseline, post-intervention (12 weeks), and follow-up (24 weeks).
Sponsors & Collaborators
-
National Sun Yat-sen University
lead OTHER
Study Design
- Allocation
- NA
- Purpose
- SUPPORTIVE_CARE
- Masking
- NONE
- Model
- SINGLE_GROUP
Eligibility
- Min Age
- 60 Years
- Sex
- ALL
- Healthy Volunteers
- No
Timeline & Regulatory
- Start
- 2026-08-01
- Primary Completion
- 2027-07-31
- Completion
- 2027-07-31
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