Bibliographic Details
| Title: |
Using mental tasks transitions detection to improve spontaneous mental activity classification. |
| Authors: |
Galán, Ferran1 Ferran.Galan@idiap.ch, Oliva, Francesc2, Guàrdia, Joan3, Galán, Ferran4 (AUTHOR), Guàrdia, Joan (AUTHOR) |
| Source: |
Medical & Biological Engineering & Computing. Jun2007, Vol. 45 Issue 6, p603-609. 7p. 1 Chart, 3 Graphs. |
| Subjects: |
Algorithms, Contact transformations, Discriminant analysis, Multivariate analysis, Computer interfaces |
| Abstract: |
This paper presents an algorithm based on canonical variates transformation (CVT) and distance based discriminant analysis (DBDA) combined with a mental tasks transitions detector (MTTD) to classify spontaneous mental activities in order to operate a brain-computer interface working under an asynchronous protocol. The algorithm won the BCI Competition III--Data Set V: Multiclass Problem, Continuous EEG--achieving an averaged classification accuracy over three subjects of 68.65% (79.60, 70.31 and 56.02%, respectively) in a three-class problem. [ABSTRACT FROM AUTHOR] |
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| Database: |
Engineering Source |
