通过单电极装置对脑电图信号进行情绪识别

M. Sarikaya, G. Ince
{"title":"通过单电极装置对脑电图信号进行情绪识别","authors":"M. Sarikaya, G. Ince","doi":"10.1109/SIU.2017.7960390","DOIUrl":null,"url":null,"abstract":"In recent years, researchers have concentrated on the development of ElectroEncephaloGraphy (EEG) based Brain-Computer Interfaces (BCI) to increase the quality of life using medical applications. BCIs can also be used for marketing, gaming, and entertainment to provide users with a more personalized experience. Both medical and non-medical applications require the ability to interpret the user's multimedia-induced perception and emotional experience. This paper presents a novel method to detect human emotion with a single-channel commercial BCI device. The proposed EEG-based emotion recognition system was tested on human test subjects using a deep learning neural network and an accuracy above 87% was achieved.","PeriodicalId":217576,"journal":{"name":"2017 25th Signal Processing and Communications Applications Conference (SIU)","volume":"76 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"13","resultStr":"{\"title\":\"Emotion recognition from EEG signals through one electrode device\",\"authors\":\"M. Sarikaya, G. Ince\",\"doi\":\"10.1109/SIU.2017.7960390\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In recent years, researchers have concentrated on the development of ElectroEncephaloGraphy (EEG) based Brain-Computer Interfaces (BCI) to increase the quality of life using medical applications. BCIs can also be used for marketing, gaming, and entertainment to provide users with a more personalized experience. Both medical and non-medical applications require the ability to interpret the user's multimedia-induced perception and emotional experience. This paper presents a novel method to detect human emotion with a single-channel commercial BCI device. The proposed EEG-based emotion recognition system was tested on human test subjects using a deep learning neural network and an accuracy above 87% was achieved.\",\"PeriodicalId\":217576,\"journal\":{\"name\":\"2017 25th Signal Processing and Communications Applications Conference (SIU)\",\"volume\":\"76 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-05-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"13\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 25th Signal Processing and Communications Applications Conference (SIU)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SIU.2017.7960390\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 25th Signal Processing and Communications Applications Conference (SIU)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SIU.2017.7960390","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 13

摘要

近年来,研究人员致力于开发基于脑电图(EEG)的脑机接口(BCI),以提高医疗应用的生活质量。bci还可以用于营销、游戏和娱乐,为用户提供更加个性化的体验。医疗和非医疗应用程序都需要能够解释用户的多媒体诱导的感知和情感体验。本文提出了一种利用单通道商用脑机接口设备检测人类情感的新方法。采用深度学习神经网络对所提出的基于脑电图的情绪识别系统进行了人体测试,准确率达到87%以上。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Emotion recognition from EEG signals through one electrode device
In recent years, researchers have concentrated on the development of ElectroEncephaloGraphy (EEG) based Brain-Computer Interfaces (BCI) to increase the quality of life using medical applications. BCIs can also be used for marketing, gaming, and entertainment to provide users with a more personalized experience. Both medical and non-medical applications require the ability to interpret the user's multimedia-induced perception and emotional experience. This paper presents a novel method to detect human emotion with a single-channel commercial BCI device. The proposed EEG-based emotion recognition system was tested on human test subjects using a deep learning neural network and an accuracy above 87% was achieved.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
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