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
Age ≥ 60 years
Capable of independent mobility (without the use of assistive devices).4
Basic ability to use a tablet or smartphone (caregivers may assist with login, but exercise must be performed by the participant).
Mini-Cog score ≥ 3.
Major cardiovascular events within the past 3 months (e.g., acute myocardial infarction, unstable angina), severe heart failure, or uncontrolled hypertension (e.g., SBP ≥ 180 or DBP ≥ 110 mmHg).
Severe osteoarticular or neuromuscular diseases that prevent the safe completion of exercise (e.g., recent hip fracture, severe Parkinsonian imbalance).
Severe psychiatric disorders or substance use disorders that may affect adherence.
Untreated moderate-to-severe obstructive sleep apnea (OSA) with extreme daytime sleepiness (the study will use objective measurements for preliminary screening).
Single group
Fit Mirror-Guided Home-Based Exercise Program
DeviceThe 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).
Multi-dimensional Sleep Health Assessment via Objective Actigraphy and Subjective Diaries
This study evaluates sleep using Buysse's (2018) Multidimensional Sleep Health framework. To address reviewer concerns regarding distinct units, the following parameters are reported separately: 1) Sleep Efficiency (%) and Duration (min), objectively monitored by ActiGraph wGT3X-BT (7-14 days per stage). 2) Sleep Regularity (min), defined as the standard deviation of the weekly sleep midpoint. 3) Sleep Timing (clock time), representing the average weekly midpoint. 4) Subjective Quality and Daytime Alertness (1-5 scale), captured via daily diaries where lower scores indicate better health. Actigraphy data are processed at 30-second epochs using ActiLife v6.13.3. This dual-track approach monitors how daytime HIIT (building sleep drive) and nighttime relaxation (reducing hyperarousal) affect specific insomnia phenotypes, overcoming the "mismatch" between subjective and objective perception. All metrics are summarized as weekly means
Multi-component Functional Physical Fitness Performance
The specific components of the physical assessment include the 30-second chair stand test to evaluate lower body strength by counting full stands from a seated position, and the 30-second arm curl test to measure upper body strength using 5-pound weights for women or 8-pound weights for men. Flexibility is assessed through the chair sit-and-reach test for the lower body and the back scratch test for the upper body, with distances measured in centimeters to determine the range of motion in the limbs. Agility and dynamic balance are recorded using the 8-foot up-and-go test, which times how quickly a participant can rise from a chair, walk 2.44 meters around a marker, and return to a seated position. Cardiorespiratory endurance is measured using either the 2-minute knee-up test, which counts total repetitions of lifting the knees to a specified height, or the 6-minute walk test, which measures the total distance traveled in meters and can be used to estimate maximal aerobic capacity.
Body Composition Analysis via Multi-Frequency Bioelectrical Impedance Analysis
Measurements are conducted in the morning, 3 hours post-meal, after emptying the bladder and avoiding vigorous exercise to prevent electrolyte and water fluctuations. Participants stand barefoot on the Tanita MC-780MA Multi-frequency Segmental Body Composition Analyzer, holding hand electrodes with arms positioned away from the torso. This assessment provides comprehensive data on basal metabolism, visceral fat index, body water, and segmental fat/muscle mass. Critically, it analyzes the Skeletal Muscle Mass Index (SMI), a key indicator for sarcopenia.
Self-Reported Demographic and Clinical Health Profile
Participants self-complete a structured questionnaire covering demographic variables (gender, height, weight, education level) and clinical history, including comorbidities such as hypertension, diabetes, cardiovascular disease, COPD, asthma, cancer, sleep apnea, stroke, or brain injury. The profile also records the frequency of lifestyle habits (smoking, alcohol, and exercise categorized as none, weekly, monthly, or yearly) and any past diagnosis of psychiatric disorders. This data ensures proper screening and baseline characterization of the study population.
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