Tracking Breathing During Sleep With Non-contact Sensors
NCT ID: NCT01680380
Last Updated: 2016-07-07
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
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WITHDRAWN
OBSERVATIONAL
2012-10-31
2016-08-31
Brief Summary
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Detailed Description
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The investigators will study the data and associated manual labeling. The investigators will develop algorithms that use statistical and machine-learning methods to train computer models designed to track breathing automatically. The investigators will compare the automatic output against manually generated labels to determine breath-tracking accuracy.
Conditions
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Study Design
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CASE_ONLY
CROSS_SECTIONAL
Study Groups
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At-Home
Overnight sleep at home
No interventions assigned to this group
Eligibility Criteria
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Inclusion Criteria
* No self-reported sleep breathing problems
Exclusion Criteria
21 Years
89 Years
ALL
Yes
Sponsors
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Oregon Health and Science University
OTHER
Responsible Party
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Alexander Kain
Assistant Professor
Principal Investigators
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Alexander Kain, Ph.D.
Role: PRINCIPAL_INVESTIGATOR
Oregon Health and Science University
Locations
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Center for Spoken Language Understanding
Portland, Oregon, United States
Countries
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Other Identifiers
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IRB00008533
Identifier Type: -
Identifier Source: org_study_id
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