M. Kedir-Talha, Sid Ahmed Walid Talha, Feriel Celia Boumghar, Karim Meddah, Hadjar Zairi
{"title":"EEG Processing System for Detecting a State of Drowsy Driving","authors":"M. Kedir-Talha, Sid Ahmed Walid Talha, Feriel Celia Boumghar, Karim Meddah, Hadjar Zairi","doi":"10.18178/ijpmbs.5.3.154-157","DOIUrl":null,"url":null,"abstract":" Abstract —By exploiting a database of 109 persons including two states to detect: sleepy or not, we have designed a system for automatically detecting drowsiness of a driver at the wheel. By filtering the alpha wave and by using the power spectral density of that same wave, our data were analyzed using the percentiles as measures of dispersion. A threshold discriminating the two states was found, which helped to highlight the area of the brain responsible for the state of drowsiness for driver. Thus, number of EEG signals to be analyzed will reduce and processing time of this system will be decreased. With cross validation technique, data are trained and tested, to get result with accuracy of 80% or higher. It shows that the EEG could be used helping experts in the development of an intelligent system for detecting state of drowsy driving with only ten signals by person.","PeriodicalId":281523,"journal":{"name":"International Journal of Pharma Medicine and Biological Sciences","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Pharma Medicine and Biological Sciences","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.18178/ijpmbs.5.3.154-157","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
Abstract —By exploiting a database of 109 persons including two states to detect: sleepy or not, we have designed a system for automatically detecting drowsiness of a driver at the wheel. By filtering the alpha wave and by using the power spectral density of that same wave, our data were analyzed using the percentiles as measures of dispersion. A threshold discriminating the two states was found, which helped to highlight the area of the brain responsible for the state of drowsiness for driver. Thus, number of EEG signals to be analyzed will reduce and processing time of this system will be decreased. With cross validation technique, data are trained and tested, to get result with accuracy of 80% or higher. It shows that the EEG could be used helping experts in the development of an intelligent system for detecting state of drowsy driving with only ten signals by person.