The University of Arizona

Linda Powers

Janet Roveda

Siteng Chen

Ao Li

Stuart Quan

Systems and methods detect cortical arousal events from a single time-varying ECG signal that is obtained via single-lead ECG. A pre-trained deep neural network transforms the ECG signal into a sequence of cortical-arousal probabilities. The deep neural network includes an inception module, a residual neural network, and a long short-term memory neural network to identify structure in the ECG signal that distinguishes periods of cortical arousal from periods without cortical arousal.

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TUCSON, AZ, United States of America

Linda Powers