Using EEG pattern analysis for implementation of game interface
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Ahn, J.-S. | - |
dc.contributor.author | Lee, W.-H. | - |
dc.date.accessioned | 2021-08-17T02:40:17Z | - |
dc.date.available | 2021-08-17T02:40:17Z | - |
dc.date.issued | 2011-06 | - |
dc.identifier.issn | 0000-0000 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/cau/handle/2019.sw.cau/48443 | - |
dc.description.abstract | In this paper, we present on EEG pattern recognition to adapt a serious game without using a game controller, which can be replaced by EEG(electroencephalography) signal research of BCI system. The feature extraction from EEG raw signal can be extracted the ERS and ERD. The features are compared frequency band by band-pass filtering after the above feature extraction steps. The average value of extracted feature signal, also it can divide two types of Support Vector Machine (SVM). Thus, the classes of divided support vectors can be input into the pattern recognition left and right direction. Also, the proposed SVM algorithm for classification will be compared with other algorithms an improved recognition rate. The recognition rate of SVM shows the increased correct rates. The highest of average recognition (success) rate is 82.45% for the discrimination of two support vectors. The experimental results of the prototype game system indicate that superiority of SVM by comparing recognition rates of the others, and it is able to apply for experimental serious games without any controllers. | - |
dc.format.extent | 4 | - |
dc.language | 영어 | - |
dc.language.iso | ENG | - |
dc.title | Using EEG pattern analysis for implementation of game interface | - |
dc.type | Article | - |
dc.identifier.doi | 10.1109/ISCE.2011.5973847 | - |
dc.identifier.bibliographicCitation | Proceedings of the International Symposium on Consumer Electronics, ISCE, pp 348 - 351 | - |
dc.description.isOpenAccess | N | - |
dc.identifier.scopusid | 2-s2.0-80052393535 | - |
dc.citation.endPage | 351 | - |
dc.citation.startPage | 348 | - |
dc.citation.title | Proceedings of the International Symposium on Consumer Electronics, ISCE | - |
dc.type.docType | Conference Paper | - |
dc.subject.keywordPlus | Average values | - |
dc.subject.keywordPlus | Band pass filtering | - |
dc.subject.keywordPlus | EEG pattern | - |
dc.subject.keywordPlus | EEG pattern recognition | - |
dc.subject.keywordPlus | Game controller | - |
dc.subject.keywordPlus | Game interfaces | - |
dc.subject.keywordPlus | Game system | - |
dc.subject.keywordPlus | Other algorithms | - |
dc.subject.keywordPlus | Raw signals | - |
dc.subject.keywordPlus | Recognition rates | - |
dc.subject.keywordPlus | Serious games | - |
dc.subject.keywordPlus | Support vector | - |
dc.subject.keywordPlus | SVM algorithm | - |
dc.subject.keywordPlus | Algorithms | - |
dc.subject.keywordPlus | Consumer electronics | - |
dc.subject.keywordPlus | Electroencephalography | - |
dc.subject.keywordPlus | Electrophysiology | - |
dc.subject.keywordPlus | Feature extraction | - |
dc.subject.keywordPlus | Frequency bands | - |
dc.subject.keywordPlus | Support vector machines | - |
dc.subject.keywordPlus | Pattern recognition systems | - |
dc.description.journalRegisteredClass | scopus | - |
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