{"title":"Personalized adaptive instruction design (PAID) for brain–computer interface using reinforcement learning and deep learning: simulated data study","authors":"A. Eliseyev, T. Aksenova","doi":"10.1080/2326263X.2019.1651570","DOIUrl":null,"url":null,"abstract":"ABSTRACTBrain–computer interface (BCI) systems may require the user to perform a set of mental tasks, such as imagining different types of motion. The performance demonstrated on these tasks varies...","PeriodicalId":45112,"journal":{"name":"Brain-Computer Interfaces","volume":"25 6 1","pages":""},"PeriodicalIF":1.8000,"publicationDate":"2019-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Brain-Computer Interfaces","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1080/2326263X.2019.1651570","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENGINEERING, BIOMEDICAL","Score":null,"Total":0}
引用次数: 4
Abstract
ABSTRACTBrain–computer interface (BCI) systems may require the user to perform a set of mental tasks, such as imagining different types of motion. The performance demonstrated on these tasks varies...
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