Non-motor tasks improve adaptive brain-computer interface performance in users with severe motor impairment

Frontiers in Neuroscience

Volumn 8, Issue OCT, 2014, Pages

  Faller, Josef ^a   Scherer, Reinhold ^a   Friedrich, Elisabeth V C ^a,b   Costa, Ursula ^c   Opisso, Eloy ^c,d   Medina, Josep ^c,d   Müller Putz, Gernot R ^a  

^a GRAZ UNIVERSITY OF TECHNOLOGY   (Austria)

^b UNIVERSITY OF CALIFORNIA   (United States)

^c University Institute affiliated with the Autonomous University of Barcelona   (Spain)

^d FUNDACIÓ INSTITUT D INVESTIGACIÓ EN CIÈNCIES DE LA SALUT GERMANS TRIAS I PUJOL   (Spain)

Author keywords

Adaptive brain computer interface (BCI); Assistive technology; Electroencephalography (EEG); Event related desynchronization (ERD); Mental tasks; Spinal cord injury (SCI); Stroke

Indexed keywords

ADAPTIVE BRAIN COMPUTER INTERFACE; ADULT; ARTICLE; ASSOCIATION; BRAIN COMPUTER INTERFACE; CEREBROVASCULAR ACCIDENT; CLINICAL ARTICLE; ELECTROENCEPHALOGRAPHY; EVOKED RESPONSE; FEMALE; HUMAN; IMAGERY; MALE; MENTAL TASK; MOTOR DYSFUNCTION; MOTOR PERFORMANCE; SEVERE MOTOR IMPAIRMENT; SPINAL CORD INJURY;

EID: 84910054253     PISSN: 16624548     EISSN: 1662453X     Source Type: Journal    
DOI: 10.3389/fnins.2014.00320     Document Type: Article

References (45)

1. Alkadhi, H., Brugger, P., Hotz Boendermaker, S., Crelier, G., Curt, A., Hepp-Reymond, M.-C., et al. (2005). What disconnection tells about motor imagery: evidence from paraplegic patients. Cereb. Cortex 15, 131-140. doi: 10.1093/cercor/bhh116
2. Allison, B. Z., Neuper, C. (2010). "Could anyone use a BCI?," in Brain-Computer Interfaces: Human-Computer Interaction Series , eds D. S. Tan and A. Nijholt (London, UK: Springer), 35-54. doi: 10.1007/978-1-84996-272-8_3
3. Ang, K. K., Guan, C., Chua, K. S. G., Ang, B. T., Kuah, C., Wang, C., et al. (2008). "A clinical evaluation on the spatial patterns of non-invasive motor imagery-based brain-computer interface in stroke," in Proc 30th Annual International IEEE EMBS Conference . (Piscataway, NJ: IEEE EMBS).
4. Ang, K. K., Guan, C., Chua, K. S. G., Ang, B. T., Kuah, C. W. K., Wang, C., et al. (2011). A large clinical study on the ability of stroke patients to use an EEG-based motor imager brain-computer interface. Clin. EEG Neurosci . 42, 253-258. doi: 10.1177/155005941104200411
5. Birbaumer, N., Ghanayim, N., Hinterberger, T., Iversen, I., Kotchoubey, B., Kübler, A., et al. (1999). A spelling device for the paralysed. Nature 398, 297-298. doi: 10.1038/18581
6. Bishop, C. M. (2007). Pattern Recognition and Machine Learning . New York, NY: Springer.
7. Blankertz, B., Losch, F., Krauledat, M., Dornhege, G., Curio, G., and Müller, K.-R. (2008). The berlin brain-computer interface: accurate performance from first-session in BCI-naive subjects. IEEE Trans. Biomed. Eng . 55, 2452-2462. doi: 10.1109/TBME.2008.923152
8. Buch, E., Weber, C., Cohen, L., Braun, C., Dimyan, M., Ard, T., et al. (2008). Think to move: a neuromagnetic brain-computer interface (BCI) system for chronic stroke. Stroke 39, 910-917. doi: 10.1161/STROKEAHA.107.505313
9. Conradi, J., Blankertz, B., Tangermann, M., Kunzmann, V., and Curio, G. (2009). Brain-computer interfacing in tetraplegic patients with high spinal cord injury. Int. J. Bioelectromagn . 11, 65-68.
10. Cramer, S. C., Elizabeth, L. R., Cohen, M. J., and Lacourse, M. G. (2007). Effects of motor imagery training after chronic, complete spinal cord injury. Exp. Brain Res . 177, 233-242. doi: 10.1007/s00221-006-0662-9
11. Curt, A., Alkadhi, H., Crelier, G. R., Hotz-Boendermaker, S., Hepp-Reymond, M.-C., and Kollias, S. S. (2002). Changes of non-affected upper limb cortical representation in paraplegic patients as assessed by fMRI. Brain 125, 2567-2578. doi: 10.1093/brain/awf250
12. Daly, J. J., and Wolpaw, J. R. (2008). Brain-computer interfaces in neurological rehabilitation. Lancet Neurol . 7, 1032-1043. doi: 10.1016/S1474-4422(08)70223-0
13. Delorme, A., Sejnowski, T., and Makeig, S. (2007). Enhanced detection of artifacts in EEG data using higher-order statistics and independent component analysis. Neuroimage 34, 1443-1449. doi: 10.1016/j.neuroimage.2006.11.004
14. Dobkin, B. H. (2004). Strategies for stroke rehabilitation. Lancet 3, 528-536. doi: 10.1016/S1474-4422(04)00851-8
15. Faller, J., Torrellas, S., Miralles, F., Holzner, C., Kapeller, C., Guger, C., et al. (2012a). "Prototype of an auto-calibrating, context-aware, hybrid brain-computer interface," in 34th Annual International Conference of the IEEE Engineering in Medicine and Biology Society . (Piscataway, NJ: IEEE EMBS).
16. Faller, J., Vidaurre, C., Solis-Escalante, T., Neuper, C., and Scherer, R. (2012b). Autocalibration and recurrent adaptation: towards a plug and play online ERD-BCI. IEEE Trans. Neural Syst. Rehabil. Eng . 20, 313-319. doi: 10.1109/TNSRE.2012.2189584
17. Friedrich, E. V. C., Scherer, R., and Neuper, C. (2012). The effect of distinct mental strategies on classification performance for brain-computer interfaces. Int. J. Psychophysiol . 84, 86-94. doi: 10.1016/j.ijpsycho.2012.01.014
18. Friedrich, E. V. C., Scherer, R., and Neuper, C. (2013). Whatever works: a systematic user-centered training protocol to optimize brain-computer interfacing individually. PLoS ONE 8:e76214. doi: 10.1371/journal.pone.0076214
19. Galán, F., Nuttin, M., Lew, E., Ferrez, P. W., Vanacker, G., Philips, J., et al. (2008). A brain-actuated wheelchair: asynchronous and non-invasive brain-computer interfaces for continuous control of robots. Clin. Neurophysiol . 119, 2159-2169. doi: 10.1016/j.clinph.2008.06.001
20. Gourab, K., and Schmit, B. D. (2010). Changes in movement-related beta-band EEG signals in human spinal cord injury. Clin. Neurophysiol . 121, 2017-2023. doi: 10.1016/j.clinph.2010.05.012
21. Grosse-Wentrup, M., Mattia, D., and Oweiss, K. (2011). Using brain-computer interfaces to induce neural plasticity and restore function. J. Neural Eng . 8:025004. doi: 10.1088/1741-2560/8/2/025004
22. Krausz, G., Scherer, R., Korisek, G., and Pfurtscheller, G. (2003). Critical decision-speed and information transfer in the "Graz Brain-Computer Interface." Appl. Psychophysiol. Biofeedback 28, 233-240. doi: 10.1023/A:1024637331493
23. Kübler, A., and Birbaumer, N. (2008). Brain-computer interfaces and communication in paralysis: extinction of goal directed thinking in completely paralysed patients? Clin. Neurophysiol . 119, 2658-2666. doi: 10.1016/j.clinph.2008.06.019
24. Kübler, A., and Neumann, N. (2005). Brain-computer interfaces - the key for the conscious brain locked into a paralyzed body. Prog. Brain Res . 150, 513-525. doi: 10.1016/S0079-6123(05)50035-9
25. Kübler, A., Neumann, N., Kaiser, J., Kotchoubey, B., Hinterberger, T., and Birbaumer, N. (2001). Brain-computer communication: self-regulation of slow cortical potentials for verbal communication. Arch. Phys. Med. Rehabil . 82, 1533-1539. doi: 10.1053/apmr.2001.26621
26. Kübler, A., Nijboer, F., Mellinger, J., Vaughan, T. M., Pawelzik, H., Schalk, G., et al. (2005). Patients with ALS can use sensorimotor rhythms to operate a braincomputer interface. Neurology 64, 1775-1777. doi: 10.1212/01.WNL.0000158616.43002.6D
27. Maynard, F. M., Bracken, M. B., Creasey, G., Ditunno, J. F., Donovan, W. H., Ducker, T. B., et al. (1997). International standards for neurological and functional classification of spinal cord injury. Spinal Cord 35, 266-274. doi: 10.1038/sj.sc.3100432
28. Millán, J., Rupp, R., Müller-Putz, G. R., Murray-Smith, R., Giugliemma, C., Tangermann, M., et al. (2010). Combining brain-computer interfaces and assistive technologies: state-of-the-art and challenges. Front. Neurosci . 4:161. doi: 10.3389/fnins.2010.00161
29. Mohapp, A., Scherer, R., Keinrath, C., Grieshofer, P., Pfurtscheller, G., and Neuper, C. (2006). "Single-trial EEG classification of executed and imagined hand movements in hemiparetic stroke patients," in Proc 3rd Int. BCI Workshop and Training Course . (Graz: Graz University of Technology Publishing House).
30. Müller-Putz, G. R., Scherer, R., Brunner, C., Leeb, R., and Pfurtscheller, G. (2008). Better than random? A closer look on BCI results. Int. J. Bioelectromagn . 10, 52-55.
31. Müller-Putz, G. R., Scherer, R., Pfurtscheller, G., and Rupp, R. (2005). EEG-based neuroprosthesis control: a step towards clinical practice. Neurosci. Lett . 382, 169-174. doi: 10.1016/j.neulet.2005.03.021
32. Neuper, C., Müller, G. R., Kübler, A., Birbaumer, N., and Pfurtscheller, G. (2003). Clinical application of an EEG-based brain-computer interface: a case study in a patient with severe motor impairment. Clin. Neurophysiol . 114, 399-409. doi: 10.1016/S1388-2457(02)00387-5
33. Neuper, C., and Pfurtscheller, G. (2001). Event-related dynamics of cortical rhythms: frequency-specific features and functional correlates. Int. J. Psychophysiol . 43, 41-58. doi: 10.1016/S0167-8760(01)00178-7
34. Obermaier, B., Müller, G. R., and Pfurtscheller, G. (2003). "Virtual keyboard" controlled by spontaneous EEG activity. IEEE Trans. Neural Syst. Rehabil. Eng . 11, 422-426. doi: 10.1109/TNSRE.2003.816866
35. Pfurtscheller, G., Guger, C., Müller, G., Krausz, G., and Neuper, C. (2000). Brain oscillations control hand orthosis in a tetraplegic. Neurosci. Lett . 292, 211-214. doi: 10.1016/S0304-3940(00)01471-3
36. Pfurtscheller, G., Linortner, P., Winkler, R., Korisek, G., and Müller-Putz, G. R. (2009). Discrimination of motor imagery-induced EEG patterns in patients with complete spinal cord injury. Comput. Intell. Neurosci . 2009:104180. doi: 10.1155/2009/104180
37. Pfurtscheller, G., and Lopes da Silva, F. H. (1999). Event-related EEG/MEG synchronization and desynchronization: basic principles. Clin. Neurophysiol . 110, 1842-1857. doi: 10.1016/S1388-2457(99)00141-8
38. Pfurtscheller, G., and Neuper, C. (2001). Motor imagery and direct brain-computer communication. Proc. IEEE 89, 1123-1134. doi: 10.1109/5.939829
39. Rohm, M., Schneiders, M., and Rupp, R. (2013). "Evaluation of MI-BCI performance in ten spinal cord injured end users," in Proc 4th TOBI Workshop 2013 (Lausanne: École Polytechnique Fédérale de Lausanne (EPFL)), 19.
40. Scherer, R., Faller, J., Balderas, D., Friedrich, E., Pröll, M., Allison, B., et al. (2013). Brain-computer interfacing: more than the sum of its parts. Soft Comput . 17, 317-331. doi: 10.1007/s00500-012-0895-4
41. Scherer, R., Lee, F., Schlögl, A., Leeb, R., Bischof, H., and Pfurtscheller, G. (2008). Toward self-paced brain-computer communication: navigation through virtual worlds. IEEE Trans. Biomed. Eng . 55, 675-682. doi: 10.1109/TBME.2007.903709
42. Sharma, N., Baron, J.-C., and Rowe, J. B. (2009). Motor imagery after stroke: relating outcome to motor network connectivity. Ann. Neurol . 66, 604-616. doi: 10.1002/ana.21810
43. Vidaurre, C., Sannelli, C., Müller, K.-R., and Blankertz, B. (2011). Co-adaptive calibration to improve BCI efficiency. J. Neural Eng . 8:025009. doi: 10.1088/1741-2560/8/2/025009
44. Vidaurre, C., Schlögl, A., Cabeza, R., Scherer, R., and Pfurtscheller, G. (2006). A fully on-line adaptive BCI. IEEE Trans. Biomed. Eng . 53, 1214-1219. doi: 10.1109/TBME.2006.873542
45. Wolpaw, J. R., and McFarland, D. J. (2004). Control of a two-dimensional movement signal by a noninvasive brain-computer interface in humans. Proc. Natl. Acad. Sci. U.S.A . 101, 17849-17854. doi: 10.1073/pnas.0403504101