Name
Title | ||
|---|---|---|
Comparison of Linear Classification Methods for P300 Brain-computer Interface on Disabled Subjects. |
Abstract | ||
|---|---|---|
In this paper, we investigate the accuracy of linear classification techniques for a P300 Brain-Computer Interface used in a typing paradigm. Fisher's Linear Discriminant Analysis (LDA), Bayesian Linear Discriminant Analysis (BLDA), Stepwise Linear Discriminant Analysis (SLDA), linear Support Vector Machine (SVM) and a method based on Feature Extraction (FE) were compared. Experiments were performed on patients suffering from Amyotrophic Lateral Sclerosis (ALS), middle cerebral artery (MCA) stroke and Subarachnoid Hemorrhage (SAH), in on-line and off-line mode. Our results show that BLDA yields a significantly higher accuracy than the other linear techniques we have compared, at least for our group of subjects. |
Year | Venue | Keywords |
|---|---|---|
2011 | BIOSIGNALS 2011 | Brain-computer interface,P300,Linear classifier,Classification accuracy,Amyotrophic lateral sclerosis,Middle cerebral artery stroke,Subarachnoid hemorrhage |
DocType | Citations | PageRank |
Conference | 0 | 0.34 |
References | Authors | |
0 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Nikolay V. Manyakov | 1 | 111 | 11.82 |
| Nikolay Chumerin | 2 | 74 | 8.42 |
| Adrien Combaz | 3 | 67 | 7.30 |
| Marc M. Van Hulle | 4 | 622 | 69.75 |