Abstract
ANIMA has as a primary objective to compare three non-conventional human computer interfaces that comply with the industrial robot ST Robotics R-17 instructions. This module, Alpha Waves Related Potentials -ARP- explains how brain waves are obtained, processed, analyzed and identified depending on their frequency. This module makes use of the Open EEG Project’s open hardware monitor for brain wave activity, called the modular EEG. The brain waves are obtained through an electrode cap complying with the international 10-20 system for electrode positioning. The brain waves are processed with a fast Fourier transform using a micro-controller and analyzed in software identifying the alpha wave’s contribution. A program identifies the amount of time that alpha wave generation was maintained through concentration, and instructions are sent to the robotic arm, executing one of four pre-defined routines. Thirty percent of the users attained control over the robotic arm with the human computer interface.
Chapter PDF
Similar content being viewed by others
Keywords
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
References
Johnston, W.: Silent Music: The Science of Meditation, p. 190. Fordham University Press, [trad.] Carmen Bustos (1997)
Transformada de Fourier: Escuela Universitaria de Ingeniería Técnica de Telecomunicación, Universidad Politécnica de Madrid (2009), http://www.diac.upm.es/acceso_profesores/asignaturas/tdi/tdi/transformadas/pdf/fourier1.pdf
Valdeavellano, M.R.: ANIMA: Métodos no convencionales de interfaz en el control de robots a través de la electroencefalografía y la electrooculografía: Módulo ocular. Universidad del Valle de Guatemala, Guatemala (2009)
Martínez, G.E.: ANIMA: Métodos no convencionales de interfaz en el control de robots a través de la electroencefalografía y la electrooculografía: Módulo motriz. Universidad del Valle de Guatemala, Guatemala (2009)
ModularEEG. OpenEEG Project (2008), http://openeeg.sourceforge.net/
Python Software Foundation. Python Programming Language (2010), http://python.org/
Open EEG Gadgets. OLIMEX Ltd. (2009), http://www.olimex.com/gadgets/index.html
Palke, A.: Brainathlon: Enhancing Brainwave Control Through Brain-Controlled Game Play, p. 37 (2003), http://www.webkitchen.com/brainathlon/files/thesis.pdf
Lee, J.C., Tan, D.S.: Using a low-cost electroencephalograph for task classification in HCI research. In: Symposium on User Interface Software and Technology on Sensing from head to toe, pp. 81–90 (2006)
Keirn, Z.A., Aunon, J.I.: A new mode of communication between man and his surroundings. IEEE Transactions on Biomedical Engineering 37(12), 1209–1214 (1990)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2010 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Reina, L.F., Martínez, G., Valdeavellano, M., Destarac, M., Esquit, C. (2010). ANIMA: Non-conventional Brain-Computer Interfaces in Robot Control through Electroencephalography and Electrooculography, ARP Module. In: Martínez-Trinidad, J.F., Carrasco-Ochoa, J.A., Kittler, J. (eds) Advances in Pattern Recognition. MCPR 2010. Lecture Notes in Computer Science, vol 6256. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15992-3_8
Download citation
DOI: https://doi.org/10.1007/978-3-642-15992-3_8
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-15991-6
Online ISBN: 978-3-642-15992-3
eBook Packages: Computer ScienceComputer Science (R0)