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Automatic detection of microsleep episodes with deep learning
[article]
2021
arXiv
pre-print
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We aimed for automatic detection of MSEs with machine learning, i.e. with deep learning based on raw EEG and EOG data as input. We analyzed MWT data of 76 patients. ...
We provide a proof of principle that it is feasible to reliably detect MSEs with deep neuronal networks based on raw EEG and EOG data with a performance close to that of human experts. ...
As a result of this work, we provide a proof of principle that reliable automatic MSE detection with deep neuronal networks working with raw EEG and EOG data as input is feasible with a quality close to ...
arXiv:2009.03027v2
fatcat:jrselwxiovdnbdfcn26oielmda
Automatic Detection of Microsleep Episodes With Deep Learning
2021
Frontiers in Neuroscience
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We aimed for automatic detection of MSEs with machine learning, i.e., with deep learning based on raw EEG and EOG data as input. We analyzed MWT data of 76 patients. ...
We provide a proof of principle that it is feasible to reliably detect MSEs with deep neuronal networks based on raw EEG and EOG data with a performance close to that of human experts. ...
and JM brought in longstanding expertise with microsleep episodes in patients, collected the data and performed visual scoring. ...
doi:10.3389/fnins.2021.564098
pmid:33841068
pmcid:PMC8024556
fatcat:z6ijlxngc5gghlksqom5k3l3e4
Automatic Detection of Microsleep Episodes With Deep Learning
2021
Preserved Fulltext
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We aimed for automatic detection of MSEs with machine learning, i.e., with deep learning based on raw EEG and EOG data as input. We analyzed MWT data of 76 patients. ...
We provide a proof of principle that it is feasible to reliably detect MSEs with deep neuronal networks based on raw EEG and EOG data with a performance close to tha [...] ...
As a result of this work, we provide a proof of principle that reliable automatic MSE detection with deep neuronal networks working with raw EEG and EOG data as input is feasible with a quality close to ...
doi:10.48350/157372
fatcat:tinx7ks2izcirlapydd627ekjy
Automatic Detection of Microsleep Episodes With Deep Learning
2021
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2022; you can also visit the original URL.
The file type is application/pdf.
We aimed for automatic detection of MSEs with machine learning, i.e., with deep learning based on raw EEG and EOG data as input. We analyzed MWT data of 76 patients. ...
We provide a proof of principle that it is feasible to reliably detect MSEs with deep neuronal networks based on raw EEG and EOG data with a performance close to that of human experts. ...
As a result of this work, we provide a proof of principle that reliable automatic MSE detection with deep neuronal networks working with raw EEG and EOG data as input is feasible with a quality close to ...
doi:10.5167/uzh-215950
fatcat:dhxjv2rapbgvbiu6i2qtgrghdq
Automatically Detected Microsleep Episodes in the Fitness-to-Drive Assessment
2020
Frontiers in Neuroscience
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Study Objectives: Microsleep episodes (MSEs) are short fragments of sleep (1-15 s) that can cause dangerous situations with potentially fatal outcomes. ...
Performance of automatic detection was compared with visual MSE scoring, following the BERN criteria, in MWT recordings of 10 participants. ...
JS and AH-G performed the data analysis and wrote the first draft of the manuscript. ...
doi:10.3389/fnins.2020.00008
pmid:32038155
pmcid:PMC6990913
fatcat:7g6ana772ffefg3ima2bgglp44
Respiratory, cardiac, EEG, BOLD signals and functional connectivity over multiple microsleep episodes
2021
NeuroImage
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By using long eyelid closures to detect microsleep onset, we showed that the onset and termination of short sleep episodes invokes a systematic sequence of BOLD signal changes that are large, widespread ...
Our findings point to the need to develop a consensus among neuroscientists using fMRI on how to deal with microsleep intrusions. ...
The study was funded by the grants NMRC/STaR/0015/2013 and STaR19may-001 provided by the National Medical Research Council (Ministry of Health, Singapore). ...
doi:10.1016/j.neuroimage.2021.118129
pmid:33951513
fatcat:fdi6rgm4ljhwbc2yrqncnathyq
EEG-Based Lapse Detection With High Temporal Resolution
2007
IEEE Transactions on Biomedical Engineering
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We have developed a system capable of detecting lapses in real-time with second-scale temporal resolution. ...
Using estimates of EEG log-power spectra from up to 4 s prior to a lapse improved detection compared with only using the most recent estimate. ...
These episodes are often termed lapses or microsleeps [5] , and indicate temporary deactivation of the cortical networks responsible for task performance [6] . ...
doi:10.1109/tbme.2007.893452
pmid:17518279
fatcat:my5jo4oxkfffvo5h2kuc6gmgsu
A Deep Learning Approach for the Segmentation of Electroencephalography Data in Eye Tracking Applications
[article]
2022
arXiv
pre-print
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Our end-to-end deep learning-based framework brings recent advances in Computer Vision to the forefront of the times series segmentation of EEG data. ...
DETRtime achieves state-of-the-art performance in ocular event detection across diverse eye-tracking experiment paradigms. ...
The proposed algorithm detects microsleep episodes in eye movement data, showing the high importance of the tool. ...
arXiv:2206.08672v1
fatcat:tzukgtvpv5ephncct4orvbxhhm
Detecting of Fatigue States of a Car Driver
[chapter]
2000
Lecture Notes in Computer Science
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This paper deals with research on fatigue states of car drivers on freeways and similar roads. All experiments are performed on-the-road. ...
The results of experiments already performed indicate that the values of symptoms evolve in cycles, which is essential to take into account during design of classifiers in the future. ...
Spectral EEG analysis is the most appropriate method for detecting the onset and different stages of sleep -but automatic evaluation of drowsiness via EEG analysis failed. ...
doi:10.1007/3-540-39949-6_32
fatcat:rmyfh7zbw5b5nkpixv4zukqlau
Automatically Detected Microsleep Episodes in the Fitness-to-Drive Assessment
2020
Preserved Fulltext
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Study Objectives: Microsleep episodes (MSEs) are short fragments of sleep (1-15 s) that can cause dangerous situations with potentially fatal outcomes. ...
Study Objectives: Microsleep episodes (MSEs) are short fragments of sleep (1-15 s) that can cause dangerous situations with potentially fatal outcomes. ...
JS and AH-G performed the data analysis and wrote the first draft of the manuscript. ...
doi:10.5167/uzh-195695
fatcat:gaflv7iaavddhielfgdixaspke
Microdream neurophenomenology
2017
Neuroscience of Consciousness
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But in the laboratory these transitions afford a unique view of how experience is transformed from the perceptually grounded consciousness of wakefulness to the hallucinatory simulations of dreaming. ...
Nightly transitions into sleep are usually uneventful and transpire in the blink of an eye. ...
Subjects commonly-sometimes adamantly-deny having slept during microsleep episodes despite clear electrophysiological (e.g. ...
doi:10.1093/nc/nix001
pmid:30042836
pmcid:PMC6007184
fatcat:56dn3xo3qzadhjhzl3ynqrck6m
A machine learning framework for space medicine predictive diagnostics with physiological signals
2013
2013 IEEE Aerospace Conference
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Prognostics and health management (PHM) in the context of space missions focuses on the fundamental issues of system failures in an attempt to predict when the failures may occur, and links these issues ...
Considering the inherent risks of space missions and the difficulty of direct communications between crew and ground support medical specialists, we see that greater autonomy in medical operations for ...
Studies have reported episodes of fatigue and the occurrence of uncontrolled sleep periods (microsleeps) in pilots [3] . ...
doi:10.1109/aero.2013.6497431
fatcat:cwmboivdrjhf3cioakc2jssvtu
Experimental sleep deprivation as a tool to test memory deficits in rodents
2013
Frontiers in Systems Neuroscience
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Studies that have accurately described methodological aspects of the SD protocol are first reviewed, followed by procedures to investigate SD-induced impairment of learning and memory consolidation in ...
The vast majority of these studies have been aimed at understanding the contribution of sleep to cognition, and in particular to memory. ...
For example, SD can never be truly "total" for extended periods of time, as episodes of "microsleep" (short episodes of intrusion of sleep into wakefulness lasting as little as a few seconds) become inevitable ...
doi:10.3389/fnsys.2013.00106
pmid:24379759
pmcid:PMC3861693
fatcat:eqcuucf3fvdlri7qjhnkhyuie4
Artificial Intellgence – Application in Life Sciences and Beyond. The Upper Rhine Artificial Intelligence Symposium UR-AI 2021
[article]
2021
arXiv
pre-print
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The TriRhenaTech alliance is a network of universities in the Upper-Rhine Trinational Metropolitan Region comprising of the German universities of applied sciences in Furtwangen, Kaiserslautern, Karlsruhe ...
Topics of the conference are applications of Artificial Intellgence in life sciences, intelligent systems, industry 4.0, mobility and others. ...
This work was funded by the Ministry of Science, Research and Arts of Baden-Württemberg (MWK) as part of the project Q-AMeLiA (Quality Assurance of Machine Learning Applications). ...
arXiv:2112.05657v1
fatcat:wdjgymicyrfybg5zth2dc2i3ni
Prediction of microsleeps using EEG inter-channel relationships
[article]
2019
Preserved Fulltext
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The aim of this study was to explore various inter-channel relationships in the electroencephalogram (EEG) for detection/prediction of microsleeps. ...
Such episodes of unresponsiveness are of particularly high importance in people who perform high-risk and monotonous activities requiring extended- attention and unimpaired visuomotor performance, such ...
The conjunction of a non-tracking episode and a video rating of deep-drowsy or lapse was labeled as microsleep. ...
doi:10.26021/1844
fatcat:5xswevuve5akdfs7uxssqxob54
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