Electroencephalography (EEG) is a non-invasive technique used to record the brain's
evoked and induced electrical activity from the scalp. Artificial intelligence, particularly …

In recent years, there has been a significant expansion in the development and use of multi-
modal sensors and technologies to monitor physical activity, sleep and circadian rhythms …

The clinical and societal measurement of human sleep has increased exponentially in
recent years. However, unlike other fields of medical analysis that have become highly …

This paper proposes a deep learning model, named DeepSleepNet, for automatic sleep
stage scoring based on raw single-channelEEG. Most of the existing methods rely on hand …

Automatic sleep staging has been often treated as a simple classification problem that aims
at determining the label of individual target polysomnography epochs one at a time. In this …

Automated evaluation of a subject's neurocognitive performance (NCP) is a relevant topic in
neurological and clinical studies. NCP represents the mental/cognitive human capacity in …

Sleep stage classification constitutes an important preliminary exam in the diagnosis of
sleep disorders. It is traditionally performed by a sleep expert who assigns to each 30 s of …

Correctly identifying sleep stages is important in diagnosing and treating sleep disorders.
This paper proposes a joint classification-and-prediction framework based on convolutional …

Background Alzheimer's disease (AD) is a progressive neurodegenerative disorder of the
brain that ultimately results in the death of neurons and dementia. The prevalence of the …

The discovery of new materials is one of the driving forces to promote the development of
modern society and technology innovation, the traditional materials research mainly …