Eeg-Based Drowsiness Analysis to Establish Driving Safety Using Deep Learning Approaches
نویسندگان
چکیده
منابع مشابه
analysis of eeg signal of drowsiness driving using chaotic features and statistical tests
electro encephalography is one of the reliable sources to detect sleep onset while driving. in this study we have tried to demonstrate that sleepiness and alertness signals are separable with an appropriate margin by extracting suitable features. so first of all we have recorded eeg signals from 10 volunteers. they were obliged to be sleep deprived about 20 hours before the test. we recorded th...
متن کاملEeg-based Drowsiness Detection Using Support Vector
......................................................................................................................ii DEDICATION ................................................................................................................... v ACKNOWLEDGEMENTS .............................................................................................. vi TABLE OF CONTENTS .................
متن کاملAutomated Drowsiness Detection For Improved Driving Safety
Several approaches were proposed for the detection and prediction of drowsiness. The approaches can be categorized as estimating the fitness of duty, modeling the sleep-wake rhythms, measuring the vehicle based performance and online operator monitoring. Computer vision based online operator monitoring approach has become prominent due to its predictive ability of detecting drowsiness. Previous...
متن کاملdriving drowsiness detection using fusion of eeg, eog and driving quality signals
this study investigates the detection of the drowsiness state for a future application such as in the reduction ofthe road traffic accidents. the electroencephalography(eeg), electrooculography (eog), driving quality (dq), and karolinska sleepiness scale (kss) data of 7 male during approximately 20 hours of sleep deprivation were recorded. to reduce the eye blink artifact, an automatic mechanis...
متن کاملEEG-based Drowsiness Detection for Safe Driving Using Chaotic Features and Statistical Tests
Electro encephalography (EEG) is one of the most reliable sources to detect sleep onset while driving. In this study, we have tried to demonstrate that sleepiness and alertness signals are separable with an appropriate margin by extracting suitable features. So, first of all, we have recorded EEG signals from 10 volunteers. They were obliged to avoid sleeping for about 20 hours before the test....
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Social Science Research Network
سال: 2022
ISSN: ['1556-5068']
DOI: https://doi.org/10.2139/ssrn.4112893