EEG-Based Alcohol Detection System for Driver Monitoring.

IF 1.2 4区 心理学 Q3 PSYCHOLOGY, MULTIDISCIPLINARY
International Journal of Psychological Research Pub Date : 2024-09-21 eCollection Date: 2024-07-01 DOI:10.21500/20112084.7434
Molly Vassbotn, Iselin J Nordstrøm-Hauge, Andres Soler, Marta Molinas
{"title":"EEG-Based Alcohol Detection System for Driver Monitoring.","authors":"Molly Vassbotn, Iselin J Nordstrøm-Hauge, Andres Soler, Marta Molinas","doi":"10.21500/20112084.7434","DOIUrl":null,"url":null,"abstract":"<p><p>Today, alcohol drinking frequently accompanies socialising as a routine activity in various groups of society. 84.0% of individuals aged 18 and above in the United States have drunk alcohol at some point in their life (National Institute on Alcohol Abuse & US, 2023). Similarly, 81.7% of Norwegians in the age group 16 to 79 have drunk alcohol in 2021 (Bye, 2018). Driving after the consumption of alcohol is a worldwide problem, causing a large number of deaths and injuries a year. This work proposes the first steps towards developing an electroencephalography (EEG)-based alcohol detector conceived with the idea to prevent people from driving under the influence of alcohol. This includes the design of an experimental protocol for EEG data collection, during which participants performed the Flanker task, and their blood alcohol concentration (BAC) was measured. The resulting data set consists of two sessions per participant, both while they are affected and not-affected by alcohol. Statistical analysis of the Flanker task indicated that participants were affected by alcohol and, therefore, their EEG signals were expected to be affected as well. The collected EEG signals were used as input for intra-subject and inter-subject models, both based on the EEGNet architecture. The intra-subject model obtained a mean classification accuracy of 90.7% and the inter-subject model a mean classification accuracy of 62.9%. The result suggest that alcohol can be detected with high accuracy when developing individual models and above the change accuracy when using a general model. Therefore, the work presented here could be used as the first steps towards the development of an EEG-based alcohol detector for drivers.</p>","PeriodicalId":46542,"journal":{"name":"International Journal of Psychological Research","volume":"17 2","pages":"91-99"},"PeriodicalIF":1.2000,"publicationDate":"2024-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11804120/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Psychological Research","FirstCategoryId":"102","ListUrlMain":"https://doi.org/10.21500/20112084.7434","RegionNum":4,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/7/1 0:00:00","PubModel":"eCollection","JCR":"Q3","JCRName":"PSYCHOLOGY, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 0

Abstract

Today, alcohol drinking frequently accompanies socialising as a routine activity in various groups of society. 84.0% of individuals aged 18 and above in the United States have drunk alcohol at some point in their life (National Institute on Alcohol Abuse & US, 2023). Similarly, 81.7% of Norwegians in the age group 16 to 79 have drunk alcohol in 2021 (Bye, 2018). Driving after the consumption of alcohol is a worldwide problem, causing a large number of deaths and injuries a year. This work proposes the first steps towards developing an electroencephalography (EEG)-based alcohol detector conceived with the idea to prevent people from driving under the influence of alcohol. This includes the design of an experimental protocol for EEG data collection, during which participants performed the Flanker task, and their blood alcohol concentration (BAC) was measured. The resulting data set consists of two sessions per participant, both while they are affected and not-affected by alcohol. Statistical analysis of the Flanker task indicated that participants were affected by alcohol and, therefore, their EEG signals were expected to be affected as well. The collected EEG signals were used as input for intra-subject and inter-subject models, both based on the EEGNet architecture. The intra-subject model obtained a mean classification accuracy of 90.7% and the inter-subject model a mean classification accuracy of 62.9%. The result suggest that alcohol can be detected with high accuracy when developing individual models and above the change accuracy when using a general model. Therefore, the work presented here could be used as the first steps towards the development of an EEG-based alcohol detector for drivers.

求助全文
约1分钟内获得全文 求助全文
来源期刊
International Journal of Psychological Research
International Journal of Psychological Research PSYCHOLOGY, MULTIDISCIPLINARY-
CiteScore
2.30
自引率
9.10%
发文量
22
审稿时长
16 weeks
期刊介绍: The International Journal of Psychological Research (Int.j.psychol.res) is the Faculty of Psychology’s official publication of San Buenaventura University in Medellin, Colombia. Int.j.psychol.res relies on a vast and diverse theoretical and thematic publishing material, which includes unpublished productions of diverse psychological issues and behavioral human areas such as psychiatry, neurosciences, mental health, among others.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信