Comprehensive Analysis of Respiratory Events Using Smartphone Systems
NCT ID: NCT03457428
Last Updated: 2019-02-26
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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TERMINATED
83 participants
OBSERVATIONAL
2017-10-31
2018-12-01
Brief Summary
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Detailed Description
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Patient awareness of this condition is growing, but obtaining adequate data has continuing barriers. The gold standard for sleep testing is the overnight clinical polysomnogram (PSG) where over 20 sensors are attached to a patient and vital signs are monitored and recorded over the course of a 6-8 hour sleep test.
This is a prospective clinical performance study to compare the ability of proprietary algorithms that analyze sleep recordings from smartphones, with FDA cleared Level III home sleep testing (HST) devices, to identify patients with obstructive sleep apnea (OSA).
Consecutive patients referred for home sleep testing (HST) for possible OSA will be offered participation. Participants who provide informed consent will fill out a questionnaire and then proceed with HST in their home. During HST, additional sound recordings will be made with either:
1. Android type smartphone with a recording application (app). The phone will be placed on a table 50-100 cm (20-40 inches) from patient's mouth.
or
2. IPhone type smartphone with a recording application (app). Phone will be placed on a table 50-100 cm (20-40 inches) from patient's mouth
The sound recordings obtained via smartphones will be analyzed electronically for OSA by the proprietary algorithms. This will be performed by engineers at Resonea, Inc., the study sponsor, who will be blinded to the results obtained by the Level III HST device
HST will be performed using a type III home sleep monitor that has been cleared by the FDA and validated to assist in the diagnosis of OSA. HST results will be interpreted according to the standards established for the device being utilized. HST tests will be interpreted by sleep medicine physicians at the study sites who will be blinded to the assessment from the proprietary algorithms.
The independently determined results of HST and proprietary algorithms analysis will then be compared.
The results of the proprietary algorithm testing will not be known to those providing HST and the proprietary algorithm analysis will not be utilized in the clinical management of study participants
The primary objectives are: (a) to demonstrate that obtaining recordings in home setting for use with the proprietary sound analysis software is feasible and safe; and (b) to compare the results of the proprietary algorithm score with HST for the diagnosis of OSA.
The secondary objectives are: (a) to compare the recorded sound data against various scoring metrics from the HST; and (b) to demonstrate that use of the sound analysis software on smartphones is feasible for patients in the home sleep setting; and (c) to use the proprietary software to identify sleep disordered breathing beyond OSA, including central sleep apnea, snoring and other conditions.
Conditions
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Study Design
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CASE_ONLY
PROSPECTIVE
Eligibility Criteria
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Inclusion Criteria
* owns/possesses a smartphone for use during the study. Must be:
* Android models running Android OS Samsung Galaxy 5 or later
* iPhone models running iOS 6 or later
Exclusion Criteria
* prior surgery for snoring or OSA
* medical contraindication of HST, as applicable
* congnitive impairment that might interfere with obtaining informed consent, or completing Clinical Questionnaire
18 Years
ALL
Yes
Sponsors
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Resonea, Inc
INDUSTRY
Responsible Party
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Jonathan Freudman
Principal Investigator
Principal Investigators
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Jon Freudman, MD
Role: PRINCIPAL_INVESTIGATOR
Resonea, Inc
Locations
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Peninsula Sleep Center
Burlingame, California, United States
Santa Monica Clinical Trials
Santa Monica, California, United States
Blue Sleep
New York, New York, United States
Sounds Sleep Health
Kirkland, Washington, United States
Countries
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References
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Karunajeewa AS, Abeyratne UR, Hukins C. Multi-feature snore sound analysis in obstructive sleep apnea-hypopnea syndrome. Physiol Meas. 2011 Jan;32(1):83-97. doi: 10.1088/0967-3334/32/1/006. Epub 2010 Nov 30.
Abeyratne UR, de Silva S, Hukins C, Duce B. Obstructive sleep apnea screening by integrating snore feature classes. Physiol Meas. 2013 Feb;34(2):99-121. doi: 10.1088/0967-3334/34/2/99. Epub 2013 Jan 23.
Other Identifiers
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CARESS
Identifier Type: -
Identifier Source: org_study_id
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