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Tracking Breathing During Sleep With Non-contact Sensors

This study has been withdrawn prior to enrollment.
(Superseded by larger funded study)
Information provided by (Responsible Party):
Alexander Kain, Oregon Health and Science University Identifier:
First received: September 4, 2012
Last updated: July 5, 2016
Last verified: July 2016
The purpose of this study is to evaluate the feasibility of tracking breathing during sleep with non-contact sensors (for example, microphones or wireless movement sensors). The investigators will use the data collected with these sensors to develop algorithms for tracking breathing during sleep. The investigators will assess the performance of the algorithms by comparing automatic output against manually-generated labels.

Sleep Apnea Syndromes Snoring

Study Type: Observational
Study Design: Observational Model: Case-Only
Time Perspective: Cross-Sectional
Official Title: Tracking Breathing During Sleep With Non-contact Sensors

Resource links provided by NLM:

Further study details as provided by Alexander Kain, Oregon Health and Science University:

Primary Outcome Measures:
  • Breathing sounds are evident in overnight audio recordings [ Time Frame: Night of recording ]
    This study aims to track breathing during sleep using a high-quality audio interface. Our primary objective is to determine if quiet breathing sounds are visible (in the spectral domain) to trained human labelers.

Enrollment: 0
Study Start Date: October 2012
Estimated Study Completion Date: August 2016
Estimated Primary Completion Date: August 2016 (Final data collection date for primary outcome measure)
Overnight sleep at home

Detailed Description:

Subjects will be asked to place non-contact sensors (for example, ambient microphones, wireless movement sensors) in their home sleep environment. No sensors will be attached to or otherwise in contact with the subject's body. The subjects will start the data collection before they fall asleep, and stop the data collection the next morning when they wake. The subjects will then return the sensors to the investigator for analysis.

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.


Ages Eligible for Study:   21 Years to 89 Years   (Adult, Senior)
Sexes Eligible for Study:   All
Accepts Healthy Volunteers:   Yes
Sampling Method:   Non-Probability Sample
Study Population
Participants will be recruited from the PI's department (OHSU faculty, Ph.D. students) by email and the investigators' personal acquaintances. Participants must be age 21-100 and have no self-reported sleep breathing problems.

Inclusion Criteria:

  • Age 21-89
  • No self-reported sleep breathing problems

Exclusion Criteria:

  • Positive diagnosis for sleep breathing problem (e.g., obstructive sleep apnea)
  Contacts and Locations
Choosing to participate in a study is an important personal decision. Talk with your doctor and family members or friends about deciding to join a study. To learn more about this study, you or your doctor may contact the study research staff using the Contacts provided below. For general information, see Learn About Clinical Studies.

Please refer to this study by its identifier: NCT01680380

United States, Oregon
Center for Spoken Language Understanding
Portland, Oregon, United States, 97239
Sponsors and Collaborators
Oregon Health and Science University
Principal Investigator: Alexander Kain, Ph.D. Oregon Health and Science University
  More Information

Responsible Party: Alexander Kain, Assistant Professor, Oregon Health and Science University Identifier: NCT01680380     History of Changes
Other Study ID Numbers: IRB00008533
Study First Received: September 4, 2012
Last Updated: July 5, 2016

Keywords provided by Alexander Kain, Oregon Health and Science University:
sleep apnea

Additional relevant MeSH terms:
Sleep Apnea Syndromes
Respiration Disorders
Respiratory Tract Diseases
Sleep Disorders, Intrinsic
Sleep Wake Disorders
Nervous System Diseases
Respiratory Sounds
Signs and Symptoms, Respiratory
Signs and Symptoms processed this record on September 18, 2017