0606 WEARABLE INNOVATION IN SLEEP: DIAGNOSIS AND TREATMENT OF OBSTRUCTIVE SLEEP APNEA

Abstract

According to the World Health Organization, Obstructive Sleep Apnea (OSA) affects more than 100 million lives worldwide, with a disturbing 80% of undiagnosed cases. For the diagnosis of OSA, Polysomnography (PSG) is considered the gold standard, however, the system is severely handicapped by its high cost (can exceed $10,000 per night along with cost of technicians and physicians), long wait times for scheduling (2–8 months), uncomfortable testing procedure, and unfamiliar testing environment. In this work, we aim at developing a low-cost, and easy to use home sleep testing device with minimum wire configuration and near clinical equivalence with the PSG system. Further, we are working towards the development of a mechanical simulator system to reverse the imminent OSA episodes based on the early prediction. Our device includes a sleep pillow with the electronics embedded inside it. A reflective type poly plethysmography signal is measured from the neck which is used to compute the heart rate, breath rate and SpO2 signals. These signals are then used as an input to our novel prediction algorithm which can predict the apnea episodes 1–3 minutes ahead with more that 90% accuracy. Two mechanical motors are attached to the pillow which can simulate the neck muscle and reverse apnea episodes. We have begun human subject testing with elderly and obese OSA and healthy control. Our device can do real-time analysis and prediction continuously for 9 hours with great user comfort. Further, the breath rate and heart rate was calculated real-time and has an average difference of 2.27 bpm and 0.31 bpm respectively compared to the PSG system. Our device is a stand-alone solution for real-time wireless OSA monitoring. Given the fact that OSA diagnosis by PSG at sleep centers can be really time-consuming and costly, our device being 10 times cheaper, comfortable and available for at home use on a daily basis can bring great value to the OSA market. This research was supported by NSF PFI-AIR-TT (National Science Foundation: Partnership for Innovation: Accelerating Innovation Research-Technology Transfer)