{"title":"A novel tactile stimulation system for BCI feedback","authors":"Kiuk Gwak, R. Leeb, J. Millán, Dae-Shik Kim","doi":"10.1109/IWW-BCI.2013.6506619","DOIUrl":null,"url":null,"abstract":"When BCI based devices are operated, users are often desired to interact with environment. However, conventional visual BCI feedback disturbs continuous and smooth interactions. Therefore, a new tactile stimulation system suitable for delivering BCI feedback to user is developed. The system employs tactile illusion of movement to produce a continuous movement within six coin motors. Two protocols that convert the BCI feedback into spatiotemporal patterns of the stimulator are tested online. The results show that there are no identified artifacts in the EEG signal and no degradation of classification accuracy.","PeriodicalId":129758,"journal":{"name":"2013 International Winter Workshop on Brain-Computer Interface (BCI)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 International Winter Workshop on Brain-Computer Interface (BCI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IWW-BCI.2013.6506619","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
When BCI based devices are operated, users are often desired to interact with environment. However, conventional visual BCI feedback disturbs continuous and smooth interactions. Therefore, a new tactile stimulation system suitable for delivering BCI feedback to user is developed. The system employs tactile illusion of movement to produce a continuous movement within six coin motors. Two protocols that convert the BCI feedback into spatiotemporal patterns of the stimulator are tested online. The results show that there are no identified artifacts in the EEG signal and no degradation of classification accuracy.