NCT06670287 · Henry Ford Health System
The Use of Multiple Sensors to Track Sleep in Nightshift Workers
(SENSE)
What this study is about
Sleep is often a challenge for nightshift workers because their work and sleep schedules are inverted. Sleep is commonly measured using actigraphy, which is the standard measure of objective sleep in the general population; however, this method has substantial limitations for nightshift workers because the standard legacy algorithms only correctly identify 50.3% of daytime sleep.
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Sleep is often a challenge for nightshift workers because their work and sleep schedules are inverted. Sleep is commonly measured using actigraphy, which is the standard measure of objective sleep in the general population; however, this method has substantial limitations for nightshift workers because the standard legacy algorithms only correctly identify 50.3% of daytime sleep. This significantly reduces the validity for nightshift workers. The purpose of this study is to test a novel method to expand actigraphy by using 1) a multi-sensor approach that 2) uses machine learning (ML) algorithms to increase the accuracy of detecting daytime sleep.
Interventions
OTHER
Single-Sensor Tracking (In-Lab)
In-lab sleep tracking using only raw accelerometer data from a single sensor collected and processed with legacy actigraphy algorithms.
OTHER
Multi-Sensor Sleep Tracking (In-Lab)
In-lab sleep tracking using raw accelerometer data and additional sensors collected and processed with machine learning.
OTHER
Multi-Sensor Sleep Tracking (At-Home)
At-home sleep tracking using raw accelerometer data and additional sensors collected and processed with machine learning.
Primary outcome measures
Sleep Continuity- Time in Bed
Time frame: Throughout study completion, up to 6 weeks
The amount of time (in minutes) a participant spends in bed from lights out to their final awakening time. All PSG variables will use standard American Academy of Sleep Medicine (AASM) sleep scoring rules. Data from the Apple Watch will have non-PSG inputs from the multi-sensor system to inform this sleep continuity variable.
Sleep Continuity- Sleep Onset Latency
Time frame: Throughout study completion, up to 6 weeks
The amount of time (in minutes) a participant takes to fall asleep, from the time of lights out, or the amount of time spent awake but attempting sleep from lights out. All PSG variables will use standard AASM sleep scoring rules; indicated with "lights out" marker on a PSG, EEG scored as wake, accompanied with a prototypical sleep posture (e.g. supine) with eyes closed. Data from the Apple Watch will have non-PSG inputs from the multi-sensor system to inform this sleep continuity variable including dim lights or darkness with lux near zero, presence in bed, rare/interspersed motion from phone and watch.
Sleep Continuity- Wake After Sleep Onset
Time frame: Throughout study completion, up to 6 weeks
The amount of time (in minutes) a participant spends awake from the time they initially falling asleep, and excluding their final wake up. All PSG variables will use standard AASM sleep scoring rules; indicated with "lights out" marker on a PSG, electroencephalography (EEG) scored as wake, accompanied with a prototypical sleep posture (e.g. supine) with eyes closed. Data from the Apple Watch will have non-PSG inputs from the multi-sensor system to inform this sleep continuity variable.
Sleep Continuity- Sleep Efficiency
Time frame: Throughout study completion, up to 6 weeks
The proportion of the total amount of time a participant is asleep of the total amount of time in bed \[(Total Sleep Time in minutes) / (Time in Bed in minutes)\]. All PSG variables will use standard AASM sleep scoring rules. Data from the Apple Watch will have non-PSG inputs from the multi-sensor system to inform this sleep continuity variable, including dim lights or darkness, presence in bed, prolonged low motion from phone and watch, breathing rate changes, and heart rate (sleep staging).
Wake
Time frame: Throughout study completion, up to 6 weeks
The amount of time (in minutes) a participant is awake \[or the absence of any type of sleep- Stage 1 (N1), Stage 2 (N2), Stage 3 (N3), Rapid Eye Movement (REM)\]. All PSG variables will use standard AASM sleep scoring rules; represented on PSG by activities prior to "lights out" marker or video monitoring (eg, video monitoring showing scrolling on social media in bed). Data from the Apple Watch will have non-PSG inputs from the multi-sensor system to inform these sleep continuity variables including motion, lights on, high heart rate.
Detection of Daytime Sleep Periods
Time frame: Throughout study completion, up to 6 weeks
Any sleep periods between 6a and 6p will be designated as daytime sleep. A daytime sleep period from the Apple Watch will be considered successfully detected if it falls within ±30 minutes of the PSG start and end times, and is at least 50% the length of the actual sleep period.
User experience
Time frame: Within two days of the at-home intervention
This will be indexed with the User Experience Questionnaire (UEQ) that has been validated for evaluation of new products and has clear and well-established benchmarks. The UEQ includes items along six domains: 1) Attractiveness (overall likability or appeal), 2) Perspicuity (learning curve and ease of use), 3) Efficiency (speed and efficiency of interactions), 4) Dependability (predictability of system behaviors), 5) Stimulation (how exciting and motivating the product is), 6) Novelty (innovation and creativity of the product).
Who can participate
This study lists these criteria on ClinicalTrials.gov. A study coordinator reviews eligibility during screening — this page does not determine whether you qualify.
Inclusion criteria
- Participants must be working a fixed nightshift schedule, operationalized as: a) working at least three night shifts a week, b) shifts must begin between 18:00 and 02:00, and last between 8 to 12 hours, and c) must also plan to maintain the nightshift schedule for the duration of the study
- Participants must have worked the nightshift for at least six months
- Must plan to maintain the nightshift schedule for the duration of the study
- Participants must be at least 18 years old
Exclusion criteria
- Termination of nightshift schedule or planned travel during the study period
- Does not have at least an average of 8-hour time bed opportunity per 24-hour period
- Unwilling to integrate the study smart sensors in their bedroom environment
- Illicit drug use via self-report and urine drug screen
- History of neurological disorders
- Alcohol use disorder
Where
- Novi, Michigan
Collaborators
Michigan State University
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Data: ClinicalTrials.gov · synced Mar 18, 2026 · Source of record for eligibility and locations