Sleep Staging

Sleep staging, the classification of sleep into distinct stages (e.g., wake, REM, non-REM), is crucial for assessing sleep quality and diagnosing sleep disorders. Current research focuses on developing accurate and robust automated sleep staging systems using various deep learning architectures, including convolutional neural networks (CNNs), recurrent neural networks (RNNs), transformers, and graph convolutional networks, often incorporating multimodal data (EEG, ECG, PPG, respiratory signals, and even video). These advancements aim to improve diagnostic efficiency and reduce the reliance on time-consuming manual scoring, ultimately impacting both clinical practice and sleep research by providing more accessible and objective sleep assessments.