Title :
Unsupervised adaptive GMM for BCI
Author :
Hasan, Bashar Awwad Shiekh ; Gan, John Q.
Author_Institution :
Brain-Comput. Interfaces Group, Univ. of Essex, Colchester
fDate :
April 29 2009-May 2 2009
Abstract :
An unsupervised adaptive Gaussian mixture model is introduced for online brain-computer interfaces (BCI). The method is tested on two BCI data sets, demonstrating significant performance improvement in comparison with a static model.
Keywords :
Gaussian distribution; brain-computer interfaces; unsupervised learning; BCI; online brain-computer interfaces; static model; unsupervised adaptive Gaussian mixture model; Adaptation model; Bayesian methods; Brain computer interfaces; Brain modeling; Electroencephalography; Gallium nitride; Neural engineering; Probability; Random variables; Testing; Gaussian mixture models; adaptive BCI; unsupervised adaptation;
Conference_Titel :
Neural Engineering, 2009. NER '09. 4th International IEEE/EMBS Conference on
Conference_Location :
Antalya
Print_ISBN :
978-1-4244-2072-8
Electronic_ISBN :
978-1-4244-2073-5
DOI :
10.1109/NER.2009.5109291
