Training protocol evaluation of a brain-computer interface: Mental tasks proposal;Evaluación de un protocolo de entrenamiento en una interfaz cerebro-computadora: Propuesta de tareas mentales

Revista de Neurologia

Volumn 47, Issue 4, 2008, Pages 197-203

  Ron Angevin, Ricardo ^a,b   Diaz Estrella A ^a  

^a UNIVERSITY OF MÁLAGA   (Spain)

^b S n   (Spain)

Author keywords

Brain computer interface; Electroencephalographic signals; Feedback; Mental task; Motor imagery; Mu rhythm; Training protocol

Indexed keywords

ADULT; ARTICLE; BRAIN COMPUTER INTERFACE; CONTROLLED STUDY; ELECTROENCEPHALOGRAM; FEEDBACK SYSTEM; FEMALE; HUMAN; HUMAN EXPERIMENT; MALE; MENTAL FUNCTION; MENTAL TASK; MOTOR PERFORMANCE; STRUCTURED QUESTIONNAIRE;

EID: 49749110780     PISSN: 02100010     EISSN: None     Source Type: Journal    
DOI: 10.33588/rn.4704.2008186     Document Type: Article

References (26)

1. Wolpaw JR, Birbaumer N, Heetderks WJ, McFarland DJ, Peckham PH, Schalk G, et al. Brain-computer interface technology: a review of the first international meeting. IEEE Trans Rehabil Eng 2000; 8: 164-73.
2. Santana D, Ramírez M, Ostrosky-Solís F. Novedades en tecnología de la rehabilitación: una revisión acerca de la interfaz cerebro-computadora. Rev Neurol 2004; 39: 447-50.
3. Pfurtscheller G, Pichler-Zlaudek K, Neuper C. ERD and ERS in voluntary movement of different limbs. In Pfurtscheller G, Lopes da Silva FH, eds. Handbook of electroencephalography and clinical neurophysiology: event related desyncronization. Amsterdam: Elsevier; 1999. p. 245-68.
4. Pfurtscheller G, Neuper C. Motor imagery activates primary sensorimotor area in humans. Neurosci Lett 1997; 239: 65-8.
5. Pfurtscheller G, Neuper C, Schlögl A, Lugger K. Separability of EEG signals recorded during right and left motor imagery using adaptative autoregressive parameters. IEEE Trans Rehabil Eng 1998; 6: 316-25.
6. Wolpaw JR, Ramoser H, McFarland DJ, Pfurtscheller G. EEG-based communication: improved accuracy by response verification. IEEE Trans Rehabil Eng 1998; 6: 326-33.
7. Guger C, Edlinger G, Harkam W, Niedermayer I, Pfurtscheller G. How many people are able to operate an EEG-based brain-computer interface (BCI)? IEEE Trans Neural Syst Rehabil Eng 2003; 11: 145-7.
8. McFarland D, McCane L, Wolpaw J. EEG-based communication and control: short-term role of feedback. IEEE Trans Rehabil Eng 1998; 6: 7-11.
9. Neuper C, Müller GR, Kübler A, Birbaumer N, Pfurtscheller G. Clinical application of an EEG-based brain-computer interface: a case study in a patient with severe motor impairment. Clin Neurophysiol 2003; 114: 399-409.
10. Cinciripini PM. Discrimination of sensorimotor EEG (12-15 Hz) activity: a comparison of response, production, and no-feedback training conditions. Psychophysiology 1984; 21: 54-62.
11. Neuper C, Schlögl A, Pfurtscheller G. Enhancement of left-right sensorimotor EEG differences during feedback-regulated motor imagery. J Clin Neurophysiol 1999; 16: 373-82.
12. Friedman D, Leeb R, Guger C, Steed A, Pfurtscheller G, Slater M. Navigating virtual reality by thought: what is it like? Presence 2007; 16: 100-10.
13. Birbaumer N, Hinterberger T, Karin A, Kübler A, Neumann N, Veit R. Brain-computer communication using self-control of slow cortical potentials (SCP). Proceedings of the 2th International Brain-Computer Interface Workshop and Training Course. Graz, Austria, septiembre 2004.
14. Birbaumer N, Kübler A, Ghanayim N, Hinterberger T, Perelmouter J, Kaiser J, et al. The thought translation device (TTD) for completely paralyzed patients. IEEE Trans Rehabil Eng 2000; 8: 190-3.
15. Hinterberger T, Schmidt S, Neumann N, Mellinger J, Blankerts B, Curio G, et al. Brain-computer communication and slow cortical potentials. IEEE Trans Biomed Eng 2004; 51: 1011-8.
16. Neumann N, Kübler A. Training locked-in patients: a challenge for the use of brain-computer interfaces. IEEE Trans Rehabil Eng 2003; 11: 169-72.
17. Santana-Vargas AD, Pérez ML, Ostrosky-Solís F. Comunicación basada en el componente P300 de los potenciales relacionados con eventos: propuesta de una matriz con imágenes. Rev Neurol 2006; 43: 653-8.
18. Curran EA, Stokes MJ. Learning to control brain activity: a review of the production and control of EEG components for driving brain-computer interface (BCI) systems. Brain Cogn 2003; 51: 326-36.
19. Curran EA, Aykacek P, Stokes MJ, Roberts SJ, Penny W, Johnsrude I, et al. Cognitive tasks for driving a brain-computer interfacing system: a pilot study. IEEE Trans Rehabil Eng 2003; 12: 48-54.
20. Obermaier B, Neuper C, Guger C, Pfurtscheller G. Information transfer rate in a five-classes brain-computer interface. IEEE Trans Rehabil Eng 2001; 9: 283-9.
21. Guger C, Schlögl A, Neuper C, Walterspacher D, Strein T, Pfurtscheller G. Rapid prototyping of an EEG-based brain-computer interface (BCI). IEEE Trans Rehabil Eng 2001; 9: 49-58.
22. Ron R, García C, Reyes A, Díaz A. Parameter study for improving training quality in brain-computer interface. Proceedings of the 2th International IASTED Conference on Biomedical Engineering. Innsbruck, Austria, febrero 2004.
23. Pfurtscheller G, Pichler-Zlaudek K, Neuper C. Quantification of ERD and ERS in the time domain. In Pfurtscheller G, Lopes da Silva FH, eds. Handbook of electroencephalography and clinical neurophysiology: event related desyncronization. Amsterdam: Elsevier; 1999. p. 89-105.
24. Bishop CM. Neural networks for pattern recognition. Oxford: Clarendon; 1995.
25. Kübler A, Kotchoubey B, Hinterberger T, Ghanayim N, Perelmouter J, Schauer M, et al. The thought translation device: a neurophysiological approach to communication in total motor paralysis. Exp Brain Res 1999; 124: 223-32.
26. Bai O, Lin P, Vorbach S, Floeter M, Hattori N, Hallett M. A high performance sensorimotor beta rhythm-based brain-computer interface associated with human natural motor behaviour. J Neural Eng 2008; 5: 24-35.