{"title":"Design and Implementation of Electro-Oculogram Based Brain-Computer-Interaction","authors":"Preeti P. Ghasad","doi":"10.1109/CICN.2016.131","DOIUrl":null,"url":null,"abstract":"HCI (Human Computer Interface) has a large scope of expansion to real life implementation. From last few years, many researchers are working on multiple body-machine interfacing techniques. Human brains generally work on electric signals transmitting all over the body and send the information to operate the body parts and eye movement recognition is independent. As we know the eye movement is most common and an essential tool for communication for paralysed patients. EOG electro-oculogram signal is used to improve the communication abilities of those patients who can move their eyes. Electro-oculogram (EOG) signal is widely and successfully used technique to detect activities of human eye. This paper presents low-cost embedded system to track eye movement for disabled persons with basic interaction with electronic devices like light bulb, fans etc. The overall project idea is to study and implement the EOG signal and transform them into the digital form so as to operate the interactive device which is next to the user.","PeriodicalId":189849,"journal":{"name":"2016 8th International Conference on Computational Intelligence and Communication Networks (CICN)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 8th International Conference on Computational Intelligence and Communication Networks (CICN)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CICN.2016.131","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
HCI (Human Computer Interface) has a large scope of expansion to real life implementation. From last few years, many researchers are working on multiple body-machine interfacing techniques. Human brains generally work on electric signals transmitting all over the body and send the information to operate the body parts and eye movement recognition is independent. As we know the eye movement is most common and an essential tool for communication for paralysed patients. EOG electro-oculogram signal is used to improve the communication abilities of those patients who can move their eyes. Electro-oculogram (EOG) signal is widely and successfully used technique to detect activities of human eye. This paper presents low-cost embedded system to track eye movement for disabled persons with basic interaction with electronic devices like light bulb, fans etc. The overall project idea is to study and implement the EOG signal and transform them into the digital form so as to operate the interactive device which is next to the user.