Quantitative evaluation of EEG-biomarkers for prediction of sleep stages
Electroencephalography (EEG) is immediate and sensitive to neurological changes
resulting from sleep stages and is considered a computing tool for understanding the …
resulting from sleep stages and is considered a computing tool for understanding the …
Interpretable and robust ai in eeg systems: A survey
The close coupling of artificial intelligence (AI) and electroencephalography (EEG) has
substantially advanced human-computer interaction (HCI) technologies in the AI era …
substantially advanced human-computer interaction (HCI) technologies in the AI era …
Inter-database validation of a deep learning approach for automatic sleep scoring
D Alvarez-Estevez, RM Rijsman - PloS one, 2021 - journals.plos.org
Study objectives Development of inter-database generalizable sleep staging algorithms
represents a challenge due to increased data variability across different datasets. Sharing …
represents a challenge due to increased data variability across different datasets. Sharing …
Decentralized data-privacy preserving deep-learning approaches for enhancing inter-database generalization in automatic sleep staging
A Anido-Alonso… - IEEE Journal of Biomedical …, 2023 - ieeexplore.ieee.org
Automatic sleep staging has been an active field of development. Despite multiple efforts,
the area remains a focus of research interest. Indeed, while promising results have reported …
the area remains a focus of research interest. Indeed, while promising results have reported …
Automatic Sleep Staging Using BiRNN with Data Augmentation and Label Redirection
Y Gong, F Wang, Y Lv, C Liu, T Li - Electronics, 2023 - mdpi.com
Sleep staging has always been a hot topic in the field of sleep medicine, and it is the
cornerstone of research on sleep problems. At present, sleep staging heavily relies on …
cornerstone of research on sleep problems. At present, sleep staging heavily relies on …
Sleep CLIP: a multimodal sleep staging model based on sleep signals and sleep staging labels
W Yang, Y Wang, J Hu, T Yuan - Sensors, 2023 - mdpi.com
Since the release of the contrastive language-image pre-training (CLIP) model designed by
the OpenAI team, it has been applied in several fields owing to its high accuracy. Sleep …
the OpenAI team, it has been applied in several fields owing to its high accuracy. Sleep …
Performance assessment of automatic sleep stage classification using only partial psg sensors
As sleep disorders are becoming overwhelmingly prevalent in industrialized countries, a
simple, readily accessible sleep stage classification technology is strikingly at need …
simple, readily accessible sleep stage classification technology is strikingly at need …
Novel welch-transform based enhanced spectro-temporal analysis for cognitive microsleep detection using a single electrode EEG
The growing demand for semi-autonomous human–machine systems has led to an
increased requirement for human fatigue detection. Direct and invasive approaches for …
increased requirement for human fatigue detection. Direct and invasive approaches for …
SleepExplain: explainable non-rapid eye movement and rapid eye movement sleep stage classification from EEG signal
Classification of sleep stages is one of the most important diagnostic approaches for a
variety of sleep-related disorders. Electroencephalography (EEG) is regarded as a powerful …
variety of sleep-related disorders. Electroencephalography (EEG) is regarded as a powerful …
Alpha anteriorization and theta posteriorization during deep sleep
Y Cui, Y Li, Q Li, J Huang, X Tan… - Journal of Neuroscience …, 2024 - Wiley Online Library
Brain states (wake, sleep, general anesthesia, etc.) are profoundly associated with the
spatiotemporal dynamics of brain oscillations. Previous studies showed that the EEG alpha …
spatiotemporal dynamics of brain oscillations. Previous studies showed that the EEG alpha …