{"title":"A Brain-Machine Interface Based on EEG: Extracted Alpha Waves Applied to Mobile Robot","authors":"M. Mahmud, D. Hawellek, Aleksander Valjamae","doi":"10.1109/AT-EQUAL.2009.17","DOIUrl":null,"url":null,"abstract":"The increasing number of signal processing tools for highly parallel neurophysiological recordings opens up new avenues for connecting technologies directly to neuronal processes. As the understanding is taking a better shape, lot more work to perform is coming up. A simple brain-machine interface may be able to reestablish the broken loop of the persons with motor dysfunction. With time the brain-machine interfacing is growing more complex due to the increased availability of instruments and processes for implementation. In this work, as a proof-of-principle we established a brain-machine interface through a few simple processes to control a robotic device using the alpha wave’s event-related synchronization and event-related de-synchronization extracted from EEG.","PeriodicalId":407640,"journal":{"name":"2009 Advanced Technologies for Enhanced Quality of Life","volume":"121 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"23","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 Advanced Technologies for Enhanced Quality of Life","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/AT-EQUAL.2009.17","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 23
Abstract
The increasing number of signal processing tools for highly parallel neurophysiological recordings opens up new avenues for connecting technologies directly to neuronal processes. As the understanding is taking a better shape, lot more work to perform is coming up. A simple brain-machine interface may be able to reestablish the broken loop of the persons with motor dysfunction. With time the brain-machine interfacing is growing more complex due to the increased availability of instruments and processes for implementation. In this work, as a proof-of-principle we established a brain-machine interface through a few simple processes to control a robotic device using the alpha wave’s event-related synchronization and event-related de-synchronization extracted from EEG.