Anatoly Bobe, Grigory Rashkov, M. Komarova, Dmitry Fastovets
{"title":"Portal: A user-friendly environment for BCI models training","authors":"Anatoly Bobe, Grigory Rashkov, M. Komarova, Dmitry Fastovets","doi":"10.1109/EnT47717.2019.9030590","DOIUrl":null,"url":null,"abstract":"This paper describes an application dedicated to noninvasive electroencephalography (EEG) signal processing and recognition. The goal of the designed software is to provide endto-end support for brain-computer interface (BCI) routines including data acquisition, signal filtering and preprocessing, feature extraction, classification and subject feedback. The software is supplied with a large number of data processing tools including ready-to-use machine learning and deep learning techniques. The real-time processing mode is also implemented.","PeriodicalId":288550,"journal":{"name":"2019 International Conference on Engineering and Telecommunication (EnT)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 International Conference on Engineering and Telecommunication (EnT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/EnT47717.2019.9030590","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
This paper describes an application dedicated to noninvasive electroencephalography (EEG) signal processing and recognition. The goal of the designed software is to provide endto-end support for brain-computer interface (BCI) routines including data acquisition, signal filtering and preprocessing, feature extraction, classification and subject feedback. The software is supplied with a large number of data processing tools including ready-to-use machine learning and deep learning techniques. The real-time processing mode is also implemented.