Abstract | ||
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The goal of this paper is to make a summary of the recent advances in electroencephalogram EEG-based brain computer interface BCI architectures developed at the Institute of Electronics Engineering and Telematics of Aveiro IEETA. First, a short overview of the most successful BCI technologies is presented and then the IEETA protocol for motor imagery non-invasive BCI for a mobile robot control is discussed. Our ongoing research on an adaptive BCI architecture that allows to autonomously adapt the BCI parameters in malfunctioning situations is also presented. 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. The proposed concept has the potential to increase the reliability of BCI systems however studies with more users are still required. |
Year | DOI | Venue |
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2013 | 10.1504/IJCISTUDIES.2013.057645 | IJCIStudies |
Field | DocType | Volume |
Mobile robot control,Computational intelligence,Simulation,Computer science,Brain–computer interface,Human–computer interaction,Artificial intelligence,Telematics,Machine learning,Electroencephalography,Motor imagery | Journal | 2 |
Issue | Citations | PageRank |
3/4 | 0 | 0.34 |
References | Authors | |
4 | 3 |
Name | Order | Citations | PageRank |
---|---|---|---|
Petia Georgieva | 1 | 81 | 17.45 |
Filipe M. T. Silva | 2 | 65 | 14.07 |
Nuno Figueiredo | 3 | 0 | 0.68 |