2017 Individual Seed Projects

Novel EEG Biomarkers of Sleep Health: A Machine Learning Study

Associate Professor (Research) of Psychiatry and Behavioral Sciences (Sleep Medicine)
Assistant Professor of Aeronautics and Astronautics and, by courtesy, of Computer Science

What is the biological correlate of subjective sleep quality? Using a variety of machine learning techniques to decode the recorded sleep of more than 5,000 adults, we will determine whether there is a single, underlying biological signal that corresponds to that feeling of restedness in the morning.

The discovery of such a biological correlate is a critical component in creating a closed-loop system to meaningfully modify an individual’s sleep health.