Multi-Sensor Sleep Tracking for Nightshift Work
(SENSE Trial)
What You Need to Know Before You Apply
What is the purpose of this trial?
This trial aims to improve sleep tracking for nightshift workers by testing a new method that uses multiple sensors and smart technology. The goal is to more accurately detect daytime sleep, often misreported with current methods. Participants will have their sleep monitored either in a lab using both single-sensor and multi-sensor methods or at home with the multi-sensor approach. The trial seeks individuals who work fixed night shifts at least three times a week and have done so for at least six months. As an unphased trial, it offers participants the opportunity to contribute to innovative research that could enhance sleep health for nightshift workers.
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 prior data suggests that this multi-sensor sleep tracking method is safe for nightshift workers?
Research has shown that using multiple sensors to track sleep is safe for nightshift workers. Studies have found that this method improves the detection of daytime sleep by 43.4%, a significant improvement over using just one sensor. No reports of harmful side effects from using multiple sensors have emerged, indicating it is well-tolerated.
The single-sensor method has been used for a long time and is generally considered safe. Although it may not be as accurate for tracking sleep in nightshift workers, it has not been linked to any major safety issues. Both methods appear safe and have been used without reports of serious risks.12345Why are researchers excited about this trial?
Researchers are excited about this trial because it explores innovative ways to track sleep quality using multiple sensors, which could be a game-changer for people working night shifts. Unlike traditional methods that rely solely on a single sensor, like a wrist-worn actigraphy device, this trial uses a combination of sensors from smart devices, including watches and phones. By harnessing advanced machine learning algorithms, the multi-sensor approach aims to provide a more comprehensive and accurate analysis of sleep patterns. This could lead to better understanding and management of sleep for those who work irregular hours, potentially improving their overall health and well-being.
What evidence suggests that this trial's methods could be effective for improving sleep tracking in nightshift workers?
This trial will compare single-sensor and multi-sensor sleep tracking methods for nightshift workers. Studies have shown that using multiple sensors with machine learning greatly improves the accuracy of sleep tracking for nightshift workers. Traditional methods, which use just one sensor, often miss much of the actual daytime sleep, accurately capturing it only about half the time. The multi-sensor approach, which participants in this trial may experience, combines data from various devices, such as watches and phones, to provide a more accurate picture. This method is particularly beneficial for nightshift workers, whose sleep patterns differ from the norm. Research indicates that this advanced system better detects when someone is truly asleep during the day, leading to more reliable results.12467
Are You a Good Fit for This Trial?
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 for a Trial Participant
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
What Are the Treatments Tested in This Trial?
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