Dusk2Dawn: an EEGLAB plugin for automatic cleaning of whole-night sleep electroencephalogram using Artifact Subspace Reconstruction
Whole-night sleep electroencephalogram (EEG) is plagued by several types of large-
amplitude artifacts. Common approaches to remove them are fraught with issues: channel …
amplitude artifacts. Common approaches to remove them are fraught with issues: channel …
Temporal evolution of neural activity and connectivity during microsleeps when rested and following sleep restriction
Even when it is critical to stay awake, such as when driving, sleep deprivation weakens
one's ability to do so by substantially increasing the propensity for microsleeps. Microsleeps …
one's ability to do so by substantially increasing the propensity for microsleeps. Microsleeps …
Predicting microsleep states using EEG inter-channel relationships
A microsleep is a brief and an involuntary sleep-related loss of consciousness of up to 15 s.
We investigated the performances of seven pairwise inter-channel relationships-covariance …
We investigated the performances of seven pairwise inter-channel relationships-covariance …
EEG-based machine learning: Theory and applications
R Shoorangiz, SJ Weddell, RD Jones - Handbook of Neuroengineering, 2023 - Springer
Electroencephalography is a widely used clinical and research method to record and
monitor the brain's electrical activity–the electroencephalogram (EEG). Machine learning …
monitor the brain's electrical activity–the electroencephalogram (EEG). Machine learning …
A Review of EEG-based Prediction of Microsleep
Microsleep is a brief, complete, and unintentional sleep-related loss of consciousness. The
duration of microsleeps andthe probability of accidents are highly correlated. In extended …
duration of microsleeps andthe probability of accidents are highly correlated. In extended …
Detection and prediction of microsleeps from EEG using Spatio-Temporal Patterns
A microsleep is a brief lapse in performance due to an involuntary sleep-related loss of
consciousness. These episodes are of particular importance in occupations requiring …
consciousness. These episodes are of particular importance in occupations requiring …
Ensemble learning based on overlapping clusters of subjects to predict microsleep states from EEG
Microsleeps are brief and involuntary instances of complete loss of sleep-related
consciousness. We present a novel approach of creating overlapping clusters of subjects …
consciousness. We present a novel approach of creating overlapping clusters of subjects …
Elektroensefalografi işaretlerinin makine öğrenmesi algoritmaları ile incelenmesi ve sınıflandırılması
Ş Bekiryazıcı - 2020 - search.proquest.com
Elektroensefalografi (EEG) işaretleri temel alınarak oluşturulan Beyin-Bilgisayar Arayüzü
araştırmaları, mevcut çalışmalardan daha yüksek sınıflandırma başarımı ve daha hızlı …
araştırmaları, mevcut çalışmalardan daha yüksek sınıflandırma başarımı ve daha hızlı …