Actively Recruiting

Phase Not Applicable
Age: 18Years +
All Genders
Healthy Volunteers
NCT06670287

The Use of Multiple Sensors to Track Sleep in Nightshift Workers

Led by Henry Ford Health System · Updated on 2026-03-18

100

Participants Needed

1

Research Sites

279 weeks

Total Duration

On this page

Sponsors

H

Henry Ford Health System

Lead Sponsor

M

Michigan State University

Collaborating Sponsor

AI-Summary

What this Trial 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. 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.

CONDITIONS

Official Title

The Use of Multiple Sensors to Track Sleep in Nightshift Workers

Who Can Participate

Age: 18Years +
All Genders
Healthy Volunteers

Eligibility Criteria

Eligible

You may qualify if you...

  • Participants must be working a fixed nightshift schedule, defined as working at least three night shifts a week
  • Night shifts must start between 18:00 and 02:00 and last 8 to 12 hours
  • Participants must have worked nightshift for at least six months
  • Participants must plan to maintain the nightshift schedule for the entire study duration
  • Participants must be at least 18 years old
Not Eligible

You will not qualify if you...

  • Termination of nightshift schedule or planned travel during the study period
  • Does not have at least an average of 8-hour time in bed opportunity per 24-hour period
  • Unwilling to use the study's smart sensors in their bedroom environment
  • Illicit drug use as reported or detected by urine drug screen
  • History of neurological disorders
  • Alcohol use disorder
  • Pregnancy

AI-Screening

AI-Powered Screening

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Trial Site Locations

Total: 1 location

1

Henry Ford Columbus Medical Center

Novi, Michigan, United States, 48377

Actively Recruiting

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Research Team

P

Philip Cheng, PhD

CONTACT

E

Elle M Wernette, PhD

CONTACT

How is the study designed?

Study Type

INTERVENTIONAL

Masking

DOUBLE

Allocation

NON_RANDOMIZED

Model

SEQUENTIAL

Primary Purpose

OTHER

Number of Arms

2

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