Sleep disordered breathing (SDB) is believed to be a widespread, under-diagnosed condition associated with detrimental health problems, at a high cost to society. The current gold standard for diagnosis of SDB is a time- consuming, expensive, and obtrusive (requiring many attached wires) sleep study, or polysomnography (PSG). The immediate objective of the proposed research is to develop and evaluate a hardware design and a set of algorithms for automatically detecting obstructive, central, or mixed apneas and hypopneas from acoustic, peripheral oxygen saturation (SpO2), and pulse rate data, using an ambient microphone and a wireless pulse oximeter. The long-term goal is to create a low-cost, easy-to-operate, minimally obtrusive, at-home device that can be used to screen for SDB in patients'homes.
Our specific aims are to: (1) develop a screening system by selecting minimally obtrusive sensor hardware and extending state-of-the art algorithms for automatically detecting SDB from acoustic, SpO2, and pulse rate data; (2) collect patient data in the sleep lab and at home from representative populations using the proposed system; (3) determine the screening accuracy by comparing the performance of the proposed system on the collected data against standard PSG-derived clinical results;and (4) measure the usability of an at-home screening device by the target population, by asking subjects who participated in the at-home data collection to complete a survey on various aspects of the setup and operation of the proposed system.
The proposed work will create a portable, low-cost, and minimally obtrusive system for automatically detecting sleep-disordered breathing, such as cessation of breathing (apnea). The system will enable early and frequent screening for sleep-disordered breathing in a patient's home, significantly increasing patient comfort while cap- turing more representative sleep data compared to a clinical sleep study requiring many attached wires.