B. Shah, Zamra Sultan, Z. Rizvi, Munnaza Iqbal, Usama Bin Zaheer, Syed Huzaif Shah, Samiya Khaliq, Shahrukh Zia, B. Khan, Sajjad Haider Zaidi
{"title":"Brain Computer Interface Implementation on Cognitive States","authors":"B. Shah, Zamra Sultan, Z. Rizvi, Munnaza Iqbal, Usama Bin Zaheer, Syed Huzaif Shah, Samiya Khaliq, Shahrukh Zia, B. Khan, Sajjad Haider Zaidi","doi":"10.1109/iCoMET48670.2020.9074097","DOIUrl":null,"url":null,"abstract":"Brain–Computer Interface (BCI) is a channel of communication between a brain and a machine. It is based on the interpretation of the electrical activity of mind and can be used to direct any external action such as control of a wheelchair. This paper discusses the development of a cost effective, efficient, non-invasive and easy to use multiclass BCI. For this self-acquired Electroencephalography (EEG) signals of different cognitive actions recorded over cerebral cortexes of different people are analyzed and then classified using Linear Discriminant Analysis (LDA). These classified signals are used to control the movement of a self-developed prototype of stretcher via a microcontroller. Stretcher in the proposed model can be replaced by any other machine and that machine can be controlled directly by brain. Hence this novel model can be used to develop brain-controlled devices for normal people as well as for People with Disability (PWD).","PeriodicalId":431051,"journal":{"name":"2020 3rd International Conference on Computing, Mathematics and Engineering Technologies (iCoMET)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 3rd International Conference on Computing, Mathematics and Engineering Technologies (iCoMET)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/iCoMET48670.2020.9074097","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
Brain–Computer Interface (BCI) is a channel of communication between a brain and a machine. It is based on the interpretation of the electrical activity of mind and can be used to direct any external action such as control of a wheelchair. This paper discusses the development of a cost effective, efficient, non-invasive and easy to use multiclass BCI. For this self-acquired Electroencephalography (EEG) signals of different cognitive actions recorded over cerebral cortexes of different people are analyzed and then classified using Linear Discriminant Analysis (LDA). These classified signals are used to control the movement of a self-developed prototype of stretcher via a microcontroller. Stretcher in the proposed model can be replaced by any other machine and that machine can be controlled directly by brain. Hence this novel model can be used to develop brain-controlled devices for normal people as well as for People with Disability (PWD).