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
See this in plain English?
AI-rewrites the medical criteria so a patient or caregiver can understand them. Always confirm with the trial site.
Multi-dimensional Sleep Health Assessment via Objective Actigraphy and Subjective Diaries
Timeframe: Assessments are conducted at three key intervals: Baseline (T0), immediately post-intervention (12 weeks, T1), and at a follow-up (24 weeks, T2).
Multi-component Functional Physical Fitness Performance
Timeframe: Assessments are conducted at three key intervals: Baseline (T0), immediately post-intervention (12 weeks, T1), and at a follow-up (24 weeks, T2).