BYU

Abstract by Chris Fortuna

Personal Infomation


Presenter's Name

Chris Fortuna

Co-Presenters

None

Degree Level

Masters

Co-Authors

None

Abstract Infomation


Department

Computer Science

Faculty Advisor

Christophe Giraud-Carrier

Title

Deep Sleep Apnea Screening With Adapted Transformer Networks

Abstract

Current methods for diagnosing Obstructive Sleep Apnea (OSA) require an expensive and intrusive overnight sleep study with expert review. Under the current system over 80% of OSA remains undiagnosed. We propose a novel screening system for diagnosing OSA accurately in the home using only pulse-oximetry data available on common smart watches and devices. We present a novel deep learning architecture for interpretable biosignals screening, inspired by SliceNet and Transformer networks.