Zihang Liang

Adaptive Time-Frequency Attention Network for Sleep Stage Classification Using Respiratory Signals

Sleep stage classification typically requires the uncomfortable and expensive polysomnography (PSG) test, which limits its widespread use in long-term monitoring and home-based environments. In this paper, we propose SleepTFANet, a novel deep learning model designed for automatic sleep stage classif…