Proposed is an easy-to-use, portable method for diagnosis of obstructive sleep apnea (OSA) using non-contact technology for use in clinical or home setting. Significance: An estimated 18 million Americans have sleep apnea and recent epidemiological studies indicate the prevalence of this disorder is on the rise. OSA is associated with several negative health outcomes including depression and type 2 diabetes. Currently, polysomnography (PSG) is the gold standard test for diagnosis of OSA. PSG systems are complex. They typically require a skilled technician for setup and continuous monitoring to ensure the accuracy of results thereby limiting their use to sleep clinics. However, recent reviews of access to sleep clinics have found supply of OSA diagnostic services not always able to meet demand. Home sleep apnea test (HSAT) systems do exist, however, like current PSG systems, they employ sensing modalities that suffer from issues of miscalibration or diminished efficacy as the user moves through the night. Sensors typically used by HSAT systems (nose worn cannula, EEG, plethysmography belts, etc.) must be in direct contact with the patient and are wired to a central recorder that the patient must wear. Patients report that worn/wired sensors are uncomfortable and in some cases affect their sleep quality. These issues present a barrier to effective diagnosis of OSA for many populations including the un/under-insured, rural populations, individuals with accessibility needs, those with developmental disabilities, and children. Hypothesis: It is hypothesized that an easy-to-use non-contact system capable of sensing standard measures of sleep apnea severity (AHI) will make available diagnosis to several populations underserved by current PSG and HSAT technology thereby increasing quality of life for those individuals effected by OSA.
Specific Aims : In the Phase I effort the proposed sensing technology was demonstrated to be exceptionally effective. In Phase II the following aims are proposed: 1) Mature the prototype hardware into a production ready system, 2) Finalize processing software and develop interfaces for end users / clinicians, and 3) Validate system performance against current state-of-the-art system in a human subject study.
An estimated 18 million Americans have sleep apnea, a disorder associated with negative health outcomes such as depression and diabetes. Recent epidemiological studies indicating that the prevalence of this disorder is on the rise. Currently, polysomnography (PSG) is the gold standard test for diagnosis of OSA however the complexity of setup and monitoring of PSG systems limit their use to sleep clinics. Home sleep apnea tests do exist. However, like current PSG systems, they make use of uncomfortable body-worn sensors that have diminished efficacy as the user moves while sleeping. Studies indicate that OSA is markedly underdiagnosed and current diagnostic equipment presents a barrier for many populations. It is hypothesized that an easy to use non-contact system capable of sensing standard measures of sleep apnea severity will make OSA diagnosis available to many populations currently underserved by PSG and HSAT technology.
