Sleep stage classification is of great significance to the diagnosis of sleep disorders.
However, existing sleep stage classification models based on deep learning are usually …

Sleep stage classification is essential in diagnosing and treating sleep disorders. Many
deep learning models have been proposed to classify sleep stages by automatic learning …

Sleep stage classification is crucial in diagnosing sleep disorders and monitoring treatment
effectiveness, yet it is inconvenient, requiring many electrodes and labor-intensive …

Objective. Computerized classification of sleep stages based on single-lead
electroencephalography (EEG) signals is important, but still challenging. In this paper, we …

Sleep stage classification based on physiological time-series is essential for sleep quality
evaluation and the diagnosis of sleep disorders in clinical practice. Existing machine …

This study proposes a novel deep learning model, called IITNet, to learn intra-and inter-
epoch temporal contexts from a raw single channel electroencephalogram (EEG) for …

Sleep is an essential human physiological behavior, and the quality of sleep directly affects
a person's physical and mental state. In clinical medicine, sleep stage is an important basis …

Automatic sleep scoring is essential for the diagnosis and treatment of sleep disorders and
enables longitudinal sleep tracking in home environments. Conventionally, learning-based …

Deep learning has achieved unprecedented success in sleep stage classification tasks,
which starts to pave the way for potential real-world applications. However, due to its …

In the inference process of existing deep learning models, it is usually necessary to process
the input data level-wise, and impose a corresponding relational inductive bias on each …