I-Corps Team: New Tool for Sleep Apnea Screening

University Of Arizona, Tucson AZ

Investigators

Abstract

The broader impact/commercial potential of this I-Corps project is to decrease health care costs for sleep apnea monitoring and diagnosis. It is estimated that a large proportion of potential sleed apnea patients are undiagnosed. Sleep apnea is a potentially remedial risk factor for hypertension, type II diabetes, stroke, coronary artery disease, and heart failure. Sleep apnea also causes learning disability among children. The proposed sleep apnea screening tool is accurate and easy to use. It can potentially be broadly employed in clinics and homes, and reduce the need for both overnight laboratory-based polysomnograms and home sleep studies. This I-Corps project targets to provide an easy-to-use screening tool for sleep apnea that combines mobile technology, internet of things (IoT) technology, and machine learning technology into one system. The core technology of this screening tool is the state-of-the-art machine learning algorithms with IoT sensors. The solution is expected to deliver a high accuracy and sensitivity sleep apnea screening methodology using deep learning methods. Preliminary results are consistent with six types of apnea-hypopnea index threshold.