| Título |
A Comparison Study of EEG Signals Classifiers for Inter-subject Generalization |
| Tipo |
Congreso |
| Sub-tipo |
Memoria |
| Descripción |
International Conference on Innovative Data Communication Technologies and Application, ICIDCA 2020
|
| Resumen |
Brain-computer interfaces are a promising technology for applications ranging from rehabilitation to video-games. A common problem for these systems is the ability to classify correctly signals corresponding to different subjects, as a consequence these systems are trained individually for each person. In this paper several classification methods, along with regularization methods, are compared, to establish a baseline for common datasets in the motor imagery paradigm for intra-subject classification and measure how they influence inter-subject classification. |
| Observaciones |
DOI 10.1007/978-3-030-77004-4_29
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
| Lugar |
Virtual, online |
| País |
Indefinido |
| No. de páginas |
305-315 |
| Vol. / Cap. |
v. 12725 LNCS |
| Inicio |
2021-06-23 |
| Fin |
2021-06-26 |
| ISBN/ISSN |
|
