Tracking Breathing During Sleep With Non-contact Sensors
Sleep Apnea Syndromes
|Study Design:||Observational Model: Case-Only
Time Perspective: Cross-Sectional
|Official Title:||Tracking Breathing During Sleep With Non-contact Sensors|
- 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.
|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
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.
Please refer to this study by its ClinicalTrials.gov identifier: NCT01680380
|United States, Oregon|
|Center for Spoken Language Understanding|
|Portland, Oregon, United States, 97239|
|Principal Investigator:||Alexander Kain, Ph.D.||Oregon Health and Science University|