@article {3105,
	title = {A comparison of regression techniques for a two-dimensional sensorimotor rhythm-based brain-computer interface.},
	journal = {Journal of neural engineering},
	volume = {7},
	year = {2010},
	month = {02/2010},
	pages = {16003},
	abstract = {People can learn to control electroencephalogram (EEG) features consisting of sensorimotor-rhythm amplitudes and use this control to move a cursor in one, two or three dimensions to a target on a video screen. This study evaluated several possible alternative models for translating these EEG features into two-dimensional cursor movement by building an offline simulation using data collected during online performance. In offline comparisons, support-vector regression (SVM) with a radial basis kernel produced somewhat better performance than simple multiple regression, the LASSO or a linear SVM. These results indicate that proper choice of a translation algorithm is an important factor in optimizing brain-computer interface (BCI) performance, and provide new insight into algorithm choice for multidimensional movement control.},
	keywords = {Young Adult},
	issn = {1741-2552},
	doi = {10.1088/1741-2560/7/1/016003},
	url = {http://www.ncbi.nlm.nih.gov/pubmed/20075503},
	author = {Fruitet, Joan and Dennis J. McFarland and Jonathan Wolpaw}
}
