Physiological radar system for diagnosing sleep disorders

Abstract

Sleep disorders are a class of medical disorders where typical sleep behavior is disrupted or abnormal, which leads to physical, mental, and emotional dysfunction. Often, sleep disorders go undiagnosed at the source of these symptoms. Sleep apnea and hypopnea are the most common sleep disorders. They are classified by a recurring interruption of breathing during sleep or abnormally shallow breathing as a result of the obstruction of the upper airway or neurological malfunction. Statistics show that about 15 million Americans suffer from obstructive sleep apnea (OSA), one type of sleep apnea. Currently, polysomnography (PSG) is considered the gold standard test for detecting sleep disorders. During this test a subject with a suspected disorder spends a night in a sleep lab, and several physiological parameters are recorded during their sleep using sensors attached to the body. All of this makes PSG time consuming, complicated, inconvenient, and expensive. Therefore, the development of more simple, accurate, comfortable, and affordable devices for sleep monitoring is desired to improve the efficacy of sleep tests and improve accessibility. In this dissertation, a non-contact physiological radar monitoring system (PRMS) is introduced for sleep disorder monitoring. This PRMS utilizes continuous-wave Doppler radar and a real-time algorithm which recognizes paradoxical breathing to diagnose OSA and hypopnea. The PRMS was integrated with a standard PSG system to evaluate the efficacy for supplementing or replacing a standard PSG test for some applications. A clinical study was carried out using the PRMS on 10 subjects with known sleep apnea. In this study, the PRMS accurately diagnosed the occurrence of either an OSA or hypopnea event, but was less effective for differentiating between them. As a compliment to a standard PSG test, the PRMS results provided a clear way to quickly identify the occurrence of an obstructive apnea/hypopnea event, with the PSG measurements then used to further analyze the event. Recognition of the occurrence of a general obstructive sleep disorders also makes the system attractive as a standalone screening device that could be conveniently used, perhaps at home, on a broad population to identify patients that should be considered for further sleep medicine treatment.