Chronic Insomnia CharacterizedDREAMSNCT07513584
Dual-track Residential Exercise With AI and Monitoring for Sleep
A study testing Fit Mirror-Guided Home-Based Exercise Program in people with Chronic Insomnia Characterized and Difficulty Falling Asleep, run by National Sun Yat-sen University.
Trial 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. Read more about this study
- Who is it for?
- Ages 60 years and older
- Conditions the study is for
- Chronic Insomnia Characterized, Difficulty Falling Asleep, Difficulty Maintaining Sleep
- What is being tested?
- Fit Mirror-Guided Home-Based Exercise Program
- Type of treatment
- Medical device
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 60 participants
- Where
- No sites listed yet
- Study dates
- 1 Aug 2026to 31 Jul 2027
- Phase
- Interventional
- Are there results?
- Not yet: the study is under way
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 60 years and older
- All sexes
- No healthy volunteers
- Adult, Older adult
Who may be able to join
- Age ≥ 60 years
- Capable of independent mobility (without the use of assistive devices).4
- Meeting one of the following sleep disturbance criteria:
- Core symptoms of DSM-5 chronic insomnia (self-reported) for ≥ 3 months. Insomnia Severity Index (ISI) ≥ 15 (moderate-to-severe insomnia). Pittsburgh Sleep Quality Index (PSQI) > 5 (poor sleep quality).
- 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.
- Consent to wear wearable devices and participate in data collection.
Who cannot join
- 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).
- Currently receiving structured psychotherapy for insomnia (e.g., CBT-I or BBTi) and not yet stabilized.
- Severe visual or hearing impairment that prevents following voice or visual instructions.
About this study
Official title: Dual-track Residential Exercise With AI and Monitoring for Sleep in Older Adults With Chronic Insomnia (DREAMS Study)
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
Read the detailed description
The DREAMS Study addresses the critical public health challenge of chronic insomnia among community-dwelling older adults (aged ≥60), which substantially impacts healthy aging and independent living. Traditional exercise interventions often suffer from suboptimal adherence and rely on subjective self-reporting that fails to capture the physiological "mismatch" between perceived and actual sleep. To get around these problems, this study uses a home-based, closed-loop, dual-track exercise recommendation model that combines wearable ActiGraph monitoring with AI-driven skeletal recognition technology (iMirror). This adaptive framework differentiates between insomnia phenotypes: daytime moderate-intensity training (HIIT or resistance exercise) is prescribed to enhance sleep drive for those with difficulty falling asleep (DFA), while nighttime relaxation training (yoga or Pilates) targets reduced hyperarousal for those with difficulty maintaining sleep (DMS). By utilizing continuous objective data, the system creates a feedback loop that dynamically adjusts exercise prescriptions (frequency, intensity, and timing), reducing the need for on-site professional supervision and ensuring safe implementation within the participant's familiar home environment. Ultimately, the DREAMS Study establishes a scalable, data-driven model for precision health promotion to inform future policies on sleep health in aging populations.
- Conditions
- Chronic Insomnia Characterized, Difficulty Falling Asleep, Difficulty Maintaining Sleep, Healthy Aging and Independent Living
- Being tested
- Fit Mirror-Guided Home-Based Exercise Program
- Keywords
- precision health promotion, insomnia phenotyping, adaptive feedback loop, wearable technology
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Fit Mirror-Guided Home-Based Exercise ProgramDevice
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).
| Study group | Role | What they receive |
|---|---|---|
| AI-Driven Dual-Track Residential Exercise and Physiological Monitoring Arm | Experimental | Participants (≥ 60) with chronic insomnia undergo a 12-week home exercise intervention followed by a 12-week follow-up. The system integrates FitMirror AI skeletal recognition for real-time guidance and ActiGraph wearable monitoring for continuous data collection. An adaptive closed-loop mechanism tailors exercise to specific insomnia phenotypes: daytime HIIT or resistance training is prescribed to enhance sleep drive for those with sleep-onset difficulties (DFA), while nighttime yoga or Pilates targets reduced hyperarousal for those with maintenance difficulties (DMS). Effectiveness is evaluated at baseline, 12 weeks, and 24 weeks using linear mixed-effects models to track improvements in multi-dimensional sleep health and functional fitness. Receives: Device: Fit Mirror-Guided Home-Based Exercise Program |
What is being measured
The primary outcome is the main question the study is designed to answer.
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
Measured: 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
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.
Measured: Assessments are conducted at three key intervals: Baseline (T0), immediately post-intervention (12 weeks, T1), and at a follow-up (24 weeks, T2).
Secondary outcomes (2)
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.
Measured: Assessments are conducted at three key intervals: Baseline (T0), immediately post-intervention (12 weeks, T1), and at a follow-up (24 weeks, T2).
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.
Measured: Collected at Baseline (T0).
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted7 Apr 2026
- Study start1 Aug 2026 (estimated)
- Primary completion31 Jul 2027 (estimated)
- Study completion31 Jul 2027 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Chronic Insomnia CharacterizedStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Interventional
- Phase
- Phase N/A
- Primary purpose
- Supportive care
- Allocation
- Not applicable
- Intervention model
- Single group
- Model description
- The DREAMS Study addresses chronic insomnia in community-dwelling older adults (≥ 60) through an AI-driven, home-based, dual-track exercise model. Integrating continuous wearable monitoring (ActiGraph) with skeletal recognition technology (FitMirror), the system creates a closed-loop feedback mechanism to overcome subjective reporting biases and adherence barriers. Intervention is tailored to insomnia phenotypes: daytime HIIT or resistance training enhances sleep drive for those with sleep-onset difficulties (DFA), while nighttime yoga or Pilates reduces hyperarousal for those with sleep-maintenance difficulties (DMS). Using a quasi-experimental design with assessments at baseline, 12 weeks (post-intervention), and 24 weeks (follow-up), the study employs linear mixed-effects models to evaluate improvements in multi-dimensional sleep health and functional fitness.
- Masking
- None (open label)
- Enrolment
- 60 participants (estimated)
Sponsor and investigators
- Lead sponsor
- National Sun Yat-sen University
- Sponsor type
- University, hospital or other
- Responsible party
- Sponsor
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07513584
- Sponsor's protocol ID
- 11501EC021
- Acronym
- DREAMS
- Status last verified
- Mar 2026
- First submitted
- 22 Mar 2026
- Last updated
- 7 Apr 2026
- Results posted
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No
Study at a glance
From the registry record, last updated by the sponsor on 7 Apr 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Dual-track Residential Exercise With AI and Monitoring for Sleep in Older Adults With Chronic Insomnia (DREAMS Study)
- ClinicalTrials.gov ID
- NCT07513584
- Acronym / sponsor ID
- DREAMS / 11501EC021
- Conditions
- Chronic Insomnia Characterized, Difficulty Falling Asleep, Difficulty Maintaining Sleep, Healthy Aging and Independent Living
- Keywords
- precision health promotion, insomnia phenotyping, adaptive feedback loop, wearable technology
- Study type
- Interventional
- Recruitment status
- Not yet recruiting
- Enrolment
- 60 participants (estimated)
- Lead sponsor
- National Sun Yat-sen UniversityUniversity, hospital or other
- Study start
- 1 Aug 2026 (estimated)
- Primary completion
- 31 Jul 2027 (estimated)
- Study completion
- 31 Jul 2027 (estimated)
- First posted
- 7 Apr 2026 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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
Detailed description
The DREAMS Study addresses the critical public health challenge of chronic insomnia among community-dwelling older adults (aged ≥60), which substantially impacts healthy aging and independent living. Traditional exercise interventions often suffer from suboptimal adherence and rely on subjective self-reporting that fails to capture the physiological "mismatch" between perceived and actual sleep. To get around these problems, this study uses a home-based, closed-loop, dual-track exercise recommendation model that combines wearable ActiGraph monitoring with AI-driven skeletal recognition technology (iMirror). This adaptive framework differentiates between insomnia phenotypes: daytime moderate-intensity training (HIIT or resistance exercise) is prescribed to enhance sleep drive for those with difficulty falling asleep (DFA), while nighttime relaxation training (yoga or Pilates) targets reduced hyperarousal for those with difficulty maintaining sleep (DMS). By utilizing continuous objective data, the system creates a feedback loop that dynamically adjusts exercise prescriptions (frequency, intensity, and timing), reducing the need for on-site professional supervision and ensuring safe implementation within the participant's familiar home environment. Ultimately, the DREAMS Study establishes a scalable, data-driven model for precision health promotion to inform future policies on sleep health in aging populations.
Study design
- Primary purpose
- Supportive care
- Allocation
- Not applicable
- Intervention model
- Single group
- Masking
- None (open label)
- Number of arms
- 1
- Model description
- The DREAMS Study addresses chronic insomnia in community-dwelling older adults (≥ 60) through an AI-driven, home-based, dual-track exercise model. Integrating continuous wearable monitoring (ActiGraph) with skeletal recognition technology (FitMirror), the system creates a closed-loop feedback mechanism to overcome subjective reporting biases and adherence barriers. Intervention is tailored to insomnia phenotypes: daytime HIIT or resistance training enhances sleep drive for those with sleep-onset difficulties (DFA), while nighttime yoga or Pilates reduces hyperarousal for those with sleep-maintenance difficulties (DMS). Using a quasi-experimental design with assessments at baseline, 12 weeks (post-intervention), and 24 weeks (follow-up), the study employs linear mixed-effects models to evaluate improvements in multi-dimensional sleep health and functional fitness.
| Arm | Type | Receives |
|---|---|---|
| AI-Driven Dual-Track Residential Exercise and Physiological Monitoring Arm | Experimental | Device: Fit Mirror-Guided Home-Based Exercise ProgramParticipants (≥ 60) with chronic insomnia undergo a 12-week home exercise intervention followed by a 12-week follow-up. The system integrates FitMirror AI skeletal recognition for real-time guidance and ActiGraph wearable monitoring for continuous data collection. An adaptive closed-loop mechanism tailors exercise to specific insomnia phenotypes: daytime HIIT or resistance training is prescribed to enhance sleep drive for those with sleep-onset difficulties (DFA), while nighttime yoga or Pilates targets reduced hyperarousal for those with maintenance difficulties (DMS). Effectiveness is evaluated at baseline, 12 weeks, and 24 weeks using linear mixed-effects models to track improvements in multi-dimensional sleep health and functional fitness. |
Who may qualify
- Ages
- 60 years and older
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
Key inclusion criteria (7 listed)
- Age ≥ 60 years
- Capable of independent mobility (without the use of assistive devices).4
- Meeting one of the following sleep disturbance criteria:
- Core symptoms of DSM-5 chronic insomnia (self-reported) for ≥ 3 months. Insomnia Severity Index (ISI) ≥ 15 (moderate-to-severe insomnia). Pittsburgh Sleep Quality Index (PSQI) > 5 (poor sleep quality).
- Basic ability to use a tablet or smartphone (caregivers may assist with login, but exercise must be performed by the participant).
Key exclusion criteria (6 listed)
- 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).
- Currently receiving structured psychotherapy for insomnia (e.g., CBT-I or BBTi) and not yet stabilized.
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| Fit Mirror-Guided Home-Based Exercise ProgramThe 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). | Device | AI-Driven Dual-Track Residential Exercise and Physiological Monitoring Arm |
Primary outcome
Multi-dimensional Sleep Health Assessment via Objective Actigraphy and Subjective Diaries
Time frame: Assessments are conducted at three key intervals: Baseline (T0), immediately post-intervention (12 weeks, T1), and at a follow-up (24 weeks, T2).
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
Time frame: Assessments are conducted at three key intervals: Baseline (T0), immediately post-intervention (12 weeks, T1), and at a follow-up (24 weeks, T2).
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.
2 secondary outcomes
Body Composition Analysis via Multi-Frequency Bioelectrical Impedance Analysis
Time frame: Assessments are conducted at three key intervals: Baseline (T0), immediately post-intervention (12 weeks, T1), and at a follow-up (24 weeks, T2).
Self-Reported Demographic and Clinical Health Profile
Time frame: Collected at Baseline (T0).
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 7 Apr 2026.
- Individual participant dataSharing planned: No
Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part.
The record lists no contact. Use the official record to reach the sponsor.
Questions about this trial
What is this clinical trial studying?
A study testing Fit Mirror-Guided Home-Based Exercise Program in people with Chronic Insomnia Characterized and Difficulty Falling Asleep, run by National Sun Yat-sen University.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 7 inclusion and 6 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: opening soon, as of the sponsor's last update on 7 Apr 2026. Status can change between updates, so confirm with the study contact before making plans.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Multi-dimensional Sleep Health Assessment via Objective Actigraphy and Subjective Diaries (time frame: Assessments are conducted at three key intervals: Baseline (T0), immediately post-intervention (12 weeks, T1), and at a follow-up (24 weeks, T2).). The study lists 2 primary outcomes in all. It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 7 Apr 2026.