Principle component feature detector for motor cortical control

Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings

Volumn 26 VI, Issue , 2004, Pages 4021-4024

  Hu, J ^a   Si, J ^a   Olson, B P ^a   He, J ^a  

^a Arizona State University   (United States)

Author keywords

Brain machine interface; Feature detection; Motor cortical control; Principle component analysis (PCA); Support vector machines (SVM)

Indexed keywords

BRAIN; ELECTRODES; ERGONOMICS; HUMAN COMPUTER INTERACTION; NEURAL NETWORKS; PRINCIPAL COMPONENT ANALYSIS;

BRAIN MACHINE INTERFACE; FEATURE DETECTION; MOTOR CORTICAL CONTROL; SUPPORT VECTOR MACHINES (SVM);

NEUROLOGY;

EID: 11144291460     PISSN: 05891019     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (4)

1. John K. Chapin and Miguel A.L. Nicolelis, "Principle component analysis of neuronal ensemble activity reveals multidimensional somatosensory representations," Journal of Neuroscience Methods, vol. 94, pp. 121-140, 1999.
2. B.P. Olson, J. Hu, J. Si, R.R Clement, and J. He, "A support vector approach to online brain control," in 25th Annual International conference of IEEE EMBS, 2003, pp. 2212-2215.
3. Keinosuke Fukunaga, Introduction to Statistical Pattern Recognition, Academic Press, INC, 1990.
4. Vladimir N. Vapnik, The nature of statistical learning theory, Springer-Verlag, New York, 1995.