Acoustic OSA Prediction During Wakefulness and Monitoring During Sleep

Study Overview
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Brief Summary
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The purpose of this study is to investigate the feasibility of sound analysis for: a) sleep apnea detection both during wakefulness and sleep, and b) flow-sound relationship during both wakefulness and sleep in patients and control individuals. The ultimate goal of our research is to simplify the current assessments for sleep apnea detection so that it is more convenient for patients and also much faster than the current techniques.

Detailed Description
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Sleep apnea, in particular obstructive sleep apnea (OSA), is one of the most common breathing disorders and is associated with major comorbidities such as higher risk perioperative complications. This is particularly concerning given that about 40-80% of people with moderate-severe OSA remain undiagnosed. Due to the resource-intensive assessments required to diagnose OSA and the significantly increased risk of car accidents and perioperative complications associated with undiagnosed OSA, there is a critical need to develop a more effective method to screen for OSA quickly and reliably. The most widely used clinical OSA screening tool is the STOP-Bang questionnaire, which is a quick and easy-to-implement inquiry form that has a high sensitivity to detect moderate and severe OSA (>93%), but it has a very high rate of false positives (>63%). Thus, a significant number of patients without OSA will continue to be referred for PSG, which contributes to a strain on the healthcare system. Therefore, a quick and reliable screening tool for OSA and its severity during wakefulness is very appealing but challenging, as people with OSA do not show any apparent symptoms during wakefulness. We have developed a novel screening algorithm for OSA based on the analysis of tracheal breathing sounds recorded from an individual during wakefulness, called AWakeOSA. It can predict OSA with a sensitivity (86%) similar to STOP-Bang, but with a much higher specificity (84%) for detecting individuals without OSA. The AWakeOSA technology still needs significant research and quality improvements to become a reliable home-care device for screening under unsupervised conditions, which is the central purpose of this project. In addition, we are interested to investigate the breathing sound changes from wakefulness to sleep in both groups of healthy and apneic population. For that, we need to record PSG data and breathing sounds during sleep in addition to recording breathing sounds during wakefulness. We have also designed a specialized hardware device, called ASAD-3, capable of recording breathing sounds with high quality during both wakefulness (short-period recording) and during sleep (long hours recording) that uses two small microphones that are placed in contact with the skin over the trachea and lung, respectively. The hardware device will be utilized to optimize the AWakeOSA algorithm and work towards achieving a reliable home-care device for screening under unsupervised conditions. The proposed technology will enable a reliable and quick diagnosis of OSA that can be either used in a clinician's office during wakefulness and/or used at home by people to monitor their own OSA. The outcomes of this study will benefit the health care system and society significantly as it will: 1) reduce the financial burden of OSA on the healthcare system by reducing the need for PSG and unnecessary preoperative resources; and 2) provide a quick and reliable personal OSA home-care monitoring system for better OSA treatment management.

Official Title
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Acoustic OSA Prediction During Wakefulness and Monitoring During Sleep

Conditions
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Obstructive Sleep Apnea

Participation Criteria
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Eligibility Criteria
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Inclusion Criteria: 1) age between 18 to 70 years. 2) suspected of OSA and referred to full PSG study by a doctor. Exclusion Criteria: 1) being diagnosed with a chronic respiratory disease including pulmonary fibrosis, emphysema, respiratory infectious disease, nocturnal asthma, obstructive pulmonary lung disease, pulmonary hypertension, congestive heart failure, sleep related hypoventilation and neuromuscular disorders. 2) having insomnia or restless leg. 3) drug addiction. 4) under the current, direct supervision of the PI of this study.

Ages Eligible for Study
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Minimum Age: 18 Years
Maximum Age: 70 Years

Sexes Eligible for Study
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All

Accepts Healthy Volunteers
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Accepts Healthy Volunteers

Study Plan
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How is the study designed?
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Arms and Interventions

| Participant Group/Arm | Intervention/Treatment |
| --- | --- |
| OSA Participants<br>Inclusion Criteria: 1) age between 18 to 70 years; 2) suspected of OSA and referred to full PSG study by a doctor. Exclusion Criteria: 1) being diagnosed with a chronic respiratory disease including pulmonary fibrosis, emphysema, respiratory infectious disease, nocturnal asthma, obstructive pulmonary lung disease, pulmonary hypertension, congestive heart failure, sleep related hypoventilation and neuromuscular disorders; 2) having insomnia or restless leg; 3) drug addiction; and 4) under the current, direct supervision of the PI of this study. | |
| Healthy Controls<br>Inclusion Criteria: 1) age between 18 to 70 years; 2) non-snorer, and being free of any sleep disorders. Exclusion Criteria: same as the OSA Participants. All participants must not have any cold or any other respiratory illness at the time of recording. Illiterate participants may still participate in the study; however, there must be a witness who is not involved in the study (i.e. PI, Co-PI, study coordinator, research assistants (RA)/students, etc.) present to witness the consent process between the participant and the individual obtaining consent. | |

What is the study measuring?
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Primary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| OSA Severity | Data recorded during wakefulness will be analyzed using our published AWakeOSA algorithm to classify the participants into two groups of those who have AHI below and above 15. We will also run Multivariate statistical analysis to find the main effect of OSA severity (AHI) on the sound features and their interaction with the anthropometric information. | 1 Day | 

Secondary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| Acoustic AHI correlation to PSG | For the sleep data, we will find the correlation of the AHI values estimated by our acoustic device using our previous algorithm compared to those of the Polysomnogram (PSG). | 1 Day | 

 Terms related to the study
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Keywords Provided by Centre Hospitalier Valida
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Obstructive Sleep Apnea, OSA, Respiratory Sound Analysis, AwakeOSA