{"title":"Online demonstration of a EEG-based drowsiness detector","authors":"Daniel Ribeiro, A. Cardoso, C. Teixeira","doi":"10.1109/EXPAT.2017.7984342","DOIUrl":null,"url":null,"abstract":"Taking a look at the number of road accidents, it's noticed that a significant part of these is due to the driver falling asleep at the wheel. This paper will descrive a Web-based plataform capable of storing, processing and analyzing eletroencephalogram (EEG) signals, thus descriving the ability to detect drowsiness that could prevent the occurrence of accidents related to driving. This Web-based platform will allow the user to test various possibilities with the use of different EEG signals, filters, window's sizes and steps, delays and classifiers, in order to find the best combination for the detection of drowsiness while driving.","PeriodicalId":283954,"journal":{"name":"2017 4th Experiment@International Conference (exp.at'17)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 4th Experiment@International Conference (exp.at'17)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/EXPAT.2017.7984342","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
Taking a look at the number of road accidents, it's noticed that a significant part of these is due to the driver falling asleep at the wheel. This paper will descrive a Web-based plataform capable of storing, processing and analyzing eletroencephalogram (EEG) signals, thus descriving the ability to detect drowsiness that could prevent the occurrence of accidents related to driving. This Web-based platform will allow the user to test various possibilities with the use of different EEG signals, filters, window's sizes and steps, delays and classifiers, in order to find the best combination for the detection of drowsiness while driving.