Sleep stage classification based on multi-level feature learning and recurrent neural networks via wearable device

摘要

Background: Automatic sleep stage classification is essential for long-term sleep monitoring. Wearable devices show more advantages than polysomnography for home use. In this paper, we propose a novel method for sleep staging using heart rate and wrist actigraphy derived from a wearable device.