COMPARISON OF LINEAR CLASSIFICATION METHODS FOR P300 BRAIN-COMPUTER INTERFACE ON DISABLED SUBJECTS

2011 ◽  
Keyword(s):  
Brain Computer Interface ◽  
Computer Interface ◽  
Classification Methods ◽  
Linear Classification

scholarly journals Comparison of Classification Methods for P300 Brain-Computer Interface on Disabled Subjects

2011 ◽  
Vol 2011 ◽  
pp. 1-12 ◽  
Author(s):  
Nikolay V. Manyakov ◽  
Nikolay Chumerin ◽  
Adrien Combaz ◽  
Marc M. Van Hulle
Keyword(s):  
Amyotrophic Lateral Sclerosis ◽  
Classification Accuracy ◽  
Brain Computer Interface ◽  
Computer Interface ◽  
Classification Methods ◽  
Linear Classifier ◽  
Typing System ◽  
The Individual ◽  
Lateral Sclerosis ◽  
Selection Of

We report on tests with a mind typing paradigm based on a P300 brain-computer interface (BCI) on a group of amyotrophic lateral sclerosis (ALS), middle cerebral artery (MCA) stroke, and subarachnoid hemorrhage (SAH) patients, suffering from motor and speech disabilities. We investigate the achieved typing accuracy given the individual patient's disorder, and how it correlates with the type of classifier used. We considered 7 types of classifiers, linear as well as nonlinear ones, and found that, overall, one type of linear classifier yielded a higher classification accuracy. In addition to the selection of the classifier, we also suggest and discuss a number of recommendations to be considered when building a P300-based typing system for disabled subjects.

Sign in / Sign up

Export Citation Format

Share Document