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Features extraction method for brain-machine communication based on the empirical mode decomposition

Autor
Diez, P.F.; Mut, V.A.; Laciar, E.; Torres, A.; Avila, E.M.
Tipus d'activitat
Article en revista
Revista
Biomedical engineering: applications, basis and communications
Data de publicació
2013-07
Volum
25
Número
2
Pàgina inicial
1
Pàgina final
13
DOI
https://doi.org/10.4015/S1016237213500580 Obrir en finestra nova
URL
http://www.worldscientific.com/doi/abs/10.4015/S1016237213500580 Obrir en finestra nova
Resum
A brain-machine interface (BMI) is a communication system that translates human brain activity into commands, and then these commands are conveyed to a machine or a computer. It is proposes a technique for features extraction from electroencephalographic (EEG) signals and afterward, their classification on different mental tasks. The empirical mode decomposition (EMD) is a method capable of processing non-stationary and nonlinear signals, as the EEG. The EMD was applied on EEG signals of seven s...
Paraules clau
Brain Computer Interface Brain Communication Systems Face Recognition Image Retrieval Signal Processing Brain-machine Interface (bmi) Empirical Mode Decomposition (emd) Feature Extraction
Grup de recerca
B2SLab - Bioinformatics and Biomedical Signals Laboratory

Participants

  • Diez, Pablo Federico  (autor)
  • Mut, Vicente A.  (autor)
  • Laciar, Eric  (autor)
  • Torres Cebrian, Abel  (autor)
  • Avila Perona, Enrique M.  (autor)