NREM sleep is the state of vigilance that best identifies the epileptogenic zone in the interictal electroencephalogram

Epilepsia ◽  
2019 ◽  
Vol 60 (12) ◽  
pp. 2404-2415 ◽  
Author(s):  
Petr Klimes ◽  
Jan Cimbalnik ◽  
Milan Brazdil ◽  
Jeffery Hall ◽  
François Dubeau ◽  
...  
Keyword(s):  
Nrem Sleep ◽  
The State ◽  
Epileptogenic Zone ◽  
State Of Vigilance

Non-Intrusive Detection of Drowsy Driving Based on Eye Tracking Data

2019 ◽  
Vol 2673 (6) ◽  
pp. 247-257 ◽  
Author(s):  
Ali Shahidi Zandi ◽  
Azhar Quddus ◽  
Laura Prest ◽  
Felix J. E. Comeau
Keyword(s):  
Eye Tracking ◽  
Motor Vehicle ◽  
Binary Classification ◽  
The State ◽  
Support Vector ◽  
Tracking Data ◽  
Drowsy Driving ◽  
Vehicle Accidents ◽  
State Of Vigilance

Drowsy driving is one of the leading causes of motor vehicle accidents in North America. This paper presents the use of eye tracking data as a non-intrusive measure of driver behavior for detection of drowsiness. Eye tracking data were acquired from 53 subjects in a simulated driving experiment, whereas the simultaneously recorded multichannel electroencephalogram (EEG) signals were used as the baseline. A random forest (RF) and a non-linear support vector machine (SVM) were employed for binary classification of the state of vigilance. Different lengths of eye tracking epoch were selected for feature extraction, and the performance of each classifier was investigated for every epoch length. Results revealed a high accuracy for the RF classifier in the range of 88.37% to 91.18% across all epoch lengths, outperforming the SVM with 77.12% to 82.62% accuracy. A feature analysis approach was presented and top eye tracking features for drowsiness detection were identified. Altogether, this study showed a high correspondence between the extracted eye tracking features and EEG as a physiological measure of vigilance and verified the potential of these features along with a proper classification technique, such as the RF, for non-intrusive long-term assessment of drowsiness in drivers. This research would ultimately lead to development of technologies for real-time assessment of the state of vigilance, providing early warning of fatigue and drowsiness in drivers.

scholarly journals Do False Predictions of Seizures Depend on the State of Vigilance? A Report from Two Seizure-Prediction Methods and Proposed Remedies

Epilepsia ◽  
2006 ◽  
Vol 47 (12) ◽  
pp. 2058-2070 ◽  
Author(s):  
Björn Schelter ◽  
Matthias Winterhalder ◽  
Thomas Maiwald ◽  
Armin Brandt ◽  
Ariane Schad ◽  
...  
Keyword(s):  
The State ◽  
Prediction Methods ◽  
Seizure Prediction ◽  
State Of Vigilance

Practical Picture Processing

1974 ◽  
Vol 32 ◽  
pp. 338-339
Author(s):  
T. A. Welton
Keyword(s):  
Radiation Damage ◽  
Coherence Length ◽  
Spatial Information ◽  
State Of The Art ◽  
Coherent Radiation ◽  
The State ◽  
Energy Spread ◽  
Electron Micrograph ◽  
Picture Processing ◽  
Molecular Skeleton

Various authors have emphasized the spatial information resident in an electron micrograph taken with adequately coherent radiation. In view of the completion of at least one such instrument, this opportunity is taken to summarize the state of the art of processing such micrographs. We use the usual symbols for the aberration coefficients, and supplement these with £ and 6 for the transverse coherence length and the fractional energy spread respectively. He also assume a weak, biologically interesting sample, with principal interest lying in the molecular skeleton remaining after obvious hydrogen loss and other radiation damage has occurred.

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