Sleep Stage Classification Based on Multi-Centers: Comparison Between Different Ages, Mental Health Conditions and Acquisition Devices.

These results suggested that when more datasets across different age groups, mental health conditions, and acquisition devices (ie, more datasets with different feature distributions for each sleep stage) are used for training, the general performance of a deep learning network will be superior for sleep stage classification tasks with varied conditions.