In this paper a new adaptive Brain Computer Interface (BCI) architecture is proposed that allows to autonomously adapt the BCI parameters in malfunctioning situations. Such situations are detected by discriminating EEG Error Potentials and when necessary the BCI mode is switched back to the training stage in order to improve its performance. First, the modules of the adaptive BCI are presented, then the scenarios for identification of the user reaction to intentionally introduced errors are discussed and finally promising preliminary results are commented. The proposed concept has the potential to increase the reliability of BCI systems. © Springer International Publishing Switzerland 2015.
Eser Adı (dc.title) | Towards and Adaptive Brain- Computer Interface- An Error Potential Approach |
Yayın Türü (dc.type) | Konferans Bildirisi |
Yazar/lar (dc.contributor.author) | FIGUEIREDO, Nuno |
Yazar/lar (dc.contributor.author) | SILVA, Filipe |
Yazar/lar (dc.contributor.author) | GEORGIEVA, Petia |
Yazar/lar (dc.contributor.author) | MILANOVA, Mariofanna |
Yazar/lar (dc.contributor.author) | MENDİ, Engin |
DOI Numarası (dc.identifier.doi) | 10.1007/978-3-319-14899-1_12 |
Atıf Dizini (dc.source.database) | Scopus |
Yayıncı (dc.publisher) | Springer Verlag |
Yayın Tarihi (dc.date.issued) | 2015 |
Kayıt Giriş Tarihi (dc.date.accessioned) | 2020-08-07T13:00:40Z |
Açık Erişim tarihi (dc.date.available) | 2020-08-07T13:00:40Z |
Kaynak (dc.source) | 3rd IAPR TC3 Workshop on Multimodal Pattern Recognition of Social Signals in Human-Computer-Interaction, MPRSS 2014 |
ISSN (dc.identifier.issn) | 03029743 (ISSN); 9783319148984 (ISBN) |
Özet (dc.description.abstract) | In this paper a new adaptive Brain Computer Interface (BCI) architecture is proposed that allows to autonomously adapt the BCI parameters in malfunctioning situations. Such situations are detected by discriminating EEG Error Potentials and when necessary the BCI mode is switched back to the training stage in order to improve its performance. First, the modules of the adaptive BCI are presented, then the scenarios for identification of the user reaction to intentionally introduced errors are discussed and finally promising preliminary results are commented. The proposed concept has the potential to increase the reliability of BCI systems. © Springer International Publishing Switzerland 2015. |
Yayın Dili (dc.language.iso) | en |
Tek Biçim Adres (dc.identifier.uri) | http://hdl.handle.net/20.500.12498/3109 |