Sleep specialists often conduct manual sleep stage scoring by visually inspecting the
patient's neurophysiological signals collected at sleep labs. This is, generally, a very difficult …

Background and objective: Proper scoring of sleep stages can give clinical information on
diagnosing patients with sleep disorders. Since traditional visual scoring of the entire sleep …

In this paper, hybrid brain-computer interface (hBCI) technologies for improving
classification accuracy and increasing the number of commands are reviewed. Hybridization …

Background Sleep staging is a critical step in a range of electrophysiological signal
processing pipelines used in clinical routine as well as in sleep research. Although the …

To facilitate the performance comparison of new methods for sleep patterns analysis,
datasets with quality content, publicly-available, are very important and useful. We introduce …

Background Automatic sleep scoring is essential owing to the fact that conventionally a large
volume of data have to be analyzed visually by the physicians which is onerous, time …

For automatic sleep stage classification, the existing methods mostly rely on hand-crafted
features selected from polysomnographic records. In this paper, the goal is to develop a …

The brain exhibits a complex temporal structure which translates into a hierarchy of distinct
neural timescales. An open question is how these intrinsic timescales are related to sensory …

Sleep staging is an important part of diagnosing the different types of sleep-related disorders
because any discrepancies in the sleep scoring process may cause serious health problems …

This work proposed a novel method for automatic sleep stage classification based on the
time, frequency, and fractional Fourier transform (FRFT) domain features extracted from a …