Multi-Sensor Sleep Tracking for Nightshift Work
(SENSE Trial)
Trial Summary
Will I have to stop taking my current medications?
The trial information does not specify whether you need to stop taking your current medications.
What data supports the effectiveness of the treatment Multi-Sensor Sleep Tracking for Nightshift Work?
Research shows that consumer-grade multi-sensor trackers, like the Fitbit Charge 2, can effectively estimate sleep patterns and behaviors in shift workers, which can help manage sleep-wake cycles better. This suggests that using such devices may help nightshift workers improve their sleep quality by aligning their rest with their natural body rhythms.12345
Is Multi-Sensor Sleep Tracking safe for humans?
How does Multi-Sensor Sleep Tracking differ from other treatments for nightshift work?
Multi-Sensor Sleep Tracking is unique because it uses multiple sensors to provide a detailed analysis of sleep patterns, which can help optimize rest-activity management for nightshift workers. Unlike traditional methods, this approach can capture variations in sleep behavior and structure, offering insights tailored to individual circadian preferences.456910
What is the purpose of this trial?
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.
Eligibility Criteria
This trial is for nightshift workers who struggle with sleep due to their inverted schedules. It's designed to test new methods of tracking sleep more accurately during the day, which traditional actigraphy fails to do.Inclusion Criteria
Exclusion Criteria
Timeline
Screening
Participants are screened for eligibility to participate in the trial
In-Lab Validation
Participants undergo in-lab validation using polysomnography to test the multi-sensor ML approach against legacy algorithms
At-Home Implementation
Participants use the multi-sensor approach for sleep tracking at home for four weeks
Follow-up
Participants are monitored for data quality and user experience feedback after the at-home implementation
Treatment Details
Interventions
- Multi-Sensor Sleep Tracking
- Single-Sensor Tracking
Find a Clinic Near You
Who Is Running the Clinical Trial?
Henry Ford Health System
Lead Sponsor
Michigan State University
Collaborator