SLEEP CLASSIFICATION BASED ON MACHINE-LEARNING MODELS

The disclosure relates to systems and methods of generating physiological state classifications such as sleep classifications. Physiological state classification may refer to a machine-learning model's prediction of a subject's physiological state based on sensor data. In particular, the machine-learning model may generate a sleep classification that represents a prediction of a subject's sleep stage. A sleep stage may refer to whether the subject is awake or asleep (for a binary classification). In some examples, the sleep stage may refer to whether the subject is awake, N1, N2, N3, and Rapid Eye Movement (REM) (for a multi-class classification).