Screening for Sleep Disordered Breathing With Minimally Obtrusive Sensors
NCT ID: NCT02470182
Last Updated: 2020-01-09
Study Results
The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.
Basic Information
Get a concise snapshot of the trial, including recruitment status, study phase, enrollment targets, and key timeline milestones.
UNKNOWN
52 participants
OBSERVATIONAL
2014-09-30
2020-06-30
Brief Summary
Review the sponsor-provided synopsis that highlights what the study is about and why it is being conducted.
Related Clinical Trials
Explore similar clinical trials based on study characteristics and research focus.
Tracking Breathing During Sleep With Non-contact Sensors
NCT01680380
Evaluating the Relationship Between Sleep-Disordered Breathing and Daytime Alertness
NCT00393913
Sleep Apnea in a Non-Clinical Population
NCT00005551
Identification of Sleep-Disordered Breathing in Children
NCT00233194
Comprehensive Analysis of Respiratory Events Using Smartphone Systems
NCT03457428
Detailed Description
Dive into the extended narrative that explains the scientific background, objectives, and procedures in greater depth.
We are looking for people interested in participating in the at-home portion of our study. We will only collect at-home data for one night of sleep per subject. After this one night, no further data collection or monitoring will occur. Subjects will be compensated for their time.
A standard sleep-breathing questionnaire (the "Berlin Questionnaire") will be administered. This questionnaire is widely used as a screening tool to determine if a person may have disordered breathing during sleep. This questionnaire consists of 10 multiple-choice questions related to snoring, daytime sleepiness, and other related conditions.
Conditions
See the medical conditions and disease areas that this research is targeting or investigating.
Study Design
Understand how the trial is structured, including allocation methods, masking strategies, primary purpose, and other design elements.
CASE_ONLY
CROSS_SECTIONAL
Study Groups
Review each arm or cohort in the study, along with the interventions and objectives associated with them.
At-Home
Overnight sleep at home (30 subjects)
No interventions assigned to this group
Sleep Lab
Overnight sleep at the OHSU sleep lab during routine polysomnography (30 subjects)
No interventions assigned to this group
Sleep Lab + At-Home
Overnight sleep at the OHSU sleep lab during routine polysomnography, followed by overnight sleep at home (30 subjects)
No interventions assigned to this group
Eligibility Criteria
Check the participation requirements, including inclusion and exclusion rules, age limits, and whether healthy volunteers are accepted.
Inclusion Criteria
* No self-reported sleep breathing problems
Exclusion Criteria
* Self-reported insomnia
* History of stroke
* Nasal or soft palate surgery in the last 12 months
* Use of a breathing assistance device (such as a CPAP machine)
21 Years
89 Years
ALL
Yes
Sponsors
Meet the organizations funding or collaborating on the study and learn about their roles.
Oregon Health and Science University
OTHER
Responsible Party
Identify the individual or organization who holds primary responsibility for the study information submitted to regulators.
Brian R Snider
Ph.D. Candidate
Principal Investigators
Learn about the lead researchers overseeing the trial and their institutional affiliations.
Jan van Santen, Ph.D.
Role: PRINCIPAL_INVESTIGATOR
Oregon Health and Science University
Locations
Explore where the study is taking place and check the recruitment status at each participating site.
Center for Spoken Language Understanding
Portland, Oregon, United States
Countries
Review the countries where the study has at least one active or historical site.
Other Identifiers
Review additional registry numbers or institutional identifiers associated with this trial.
IRB00010124
Identifier Type: -
Identifier Source: org_study_id
More Related Trials
Additional clinical trials that may be relevant based on similarity analysis.