Individual characteristics and their effect on predicting Mu rhythm modulation

International Journal of Human-Computer Interaction

Volumn 27, Issue 1, 2011, Pages 24-37

  Randolph, Adriane B ^a   Jackson, Melody Moore ^b   Karmakar, Saurav ^c  

^a KENNESAW STATE UNIVERSITY   (United States)

^b GEORGIA INSTITUTE OF TECHNOLOGY   (United States)

^c GEORGIA STATE UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 78650814767     PISSN: 10447318     EISSN: 15327590     Source Type: Journal    
DOI: 10.1080/10447318.2011.535750     Document Type: Article

References (35)

1. Allison, B. Z. (2009). The I of BCIs: Next Generation Interfaces for Brain-Computer Interface Systems That Adapt to Individual Users. Paper presented at the 13th International Conference on Human-Computer Interaction, July 2009, San Diego, CA. Part II: Novel Interaction Methods and Techniques.
2. Allison, B., Luth, T., Valbuena, D., Teymourian, A., Volosyak, I., & Graeser, A. (2010). BCI demographics: How many (and what kinds of) people can use an SSVEP BCI? IEEE Transactions on Neural Systems and Rehabilitation Engineering, 107-116.
3. Beek, H. (1958). Age and the central rhythm "en arceau" [Abstract]. Electroencephalogry and Clinical Neurophysiology, 10, 356.
4. Gastaut, H. (1952). Electrocorticographic study of the reactivity of Rolandic rhythm [French]. Revue Neurologique (Paris), 87, 176-182.
5. Graimann, B., Allison, B., Mandel, C., Lüth, T., Valbuena, D., & Gräser, A. (2008). Non-invasive brain-computer interfaces for semi-autonomous assistive devices. In Robust intelligent systems (pp. 113-138), London, UK: Springer.
6. Guger, C., Daban, S., Sellers, E., Holzner, C., Krausz, G., Carabalona, R.,... Edlinger, G. (2009). How many people are able to control a P300-based brain-computer interface (BCI)? Neuroscience Letters, 462(1), 94-98.
7. Hair, J. F., Jr., Anderson, R. E., Tatham, R. L., & Black, W. C. (1998). Multivariate data analysis with readings, 5th edition. Englewood Cliffs, NJ: Prentice Hall.
8. Iturrate, I., Antelis, J., Minguez, J., & Kuebler, A. (2009). Non-invasive brain-actuated wheelchair based on a P300 neurophysiological protocol and automated navigation. IEEE Transactions on Robotics, 25, 614-627.
9. Kennedy, P. R., & Adams, K. D. (2003). A decision tree for brain-computer interface devices. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 11, 148-150.
10. Kübler, A., & Birbaumer, N. (2008). Brain-computer interfaces and communication in paralysis: Extinction of goal directed thinking in completely paralysed patients? Clinical Neurophysiology, 119, 2658-2666.
11. Maiese, K. (2008). Locked-in syndrome. In The Merck Manual's online medical library. Whitehouse Station, NJ: Merck. Retrieved from http://www.merck.com/mmpe/sec16/ ch212/ch212c.html
12. McFarland, D. J., Miner, L. A., Vaughan, T. M., & Wolpaw, J. R. (2000). Mu and beta rhythm topographies during motor imagery and actual movements. Brain Topography, 12, 177-186.
13. Montgomery, D. C., Peck, E. A., & Vinning, G. G. (2001). Introduction to linear regression analysis (3rd ed.). New York, NY: Wiley.
14. Moore, M. M. (2003). Real-world applications for brain-computer interface technology. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 11, 162-165.
15. Moore, M. M., & Dua, U. (2004, October). A galvanic skin response interface for people with severe motor disabilities. Paper presented at the the Sixth International ACM SIGACCESS Conference on Computers and Accessibility (ASSETS), Atlanta, GA.
16. Moore, M. M., Storey, V. C., & Randolph, A. B. (2005). User profiles for facilitating conversations with locked-in users. Paper presented at the International Conference for Information Systems, Las Vegas, December 2009.
17. Moore, M. M., Tomori, O., & Yadav, A. (2004, October). The BrainBrowser: A brain computer interface for internet navigation. Paper presented at the Neuroscience 2004: The 34th Annual Meeting of the Society for Neuroscience, San Diego, CA.
18. Nam, C. S., Jeon, Y., Li, Y., Kim, Y.-J., & Yoon, H.-Y. (2009). Usability of the P300 Speller: Towards a more sustainable brain-computer interface. e-Minds: International Journal on Human-Computer Interaction, 1(5), 111-125.
19. National Institute of Neurological Disorders and Stroke. (2007). Locked-in syndrome. Bethesda, MD: National Institutes of Health.
20. Niedermeyer, E., & Koshino, Y. (1975). Enhancement of rolandic mu-rhythm by pattern vision. Electroencephalography and Clinical Neurophysiology, 38, 535-538.
21. Niedermeyer, E., & Lopes da Silva, F. H. (2005). Electroencephalography: Basic principles, clinical applications, and related fields. Philadelphia, PA: Lippincott Williams & Wilkins.
22. Petersén, I., & Eeg-Olofsson, O. (1971). The development of the electroencephalogram in normal children from the age of 1 through 15 years-Paroxysmal activity. Neuropadiatrie, 2,247-304.
23. Randolph, A. B. (2008). An expert system for matching individual characteristics and features of brain-computer interface technologies with performance. Paper presented at the SIGCHI Conference Workshop on Brain-Computer Interfaces for HCI and Games, April 2008, Florence, Italy.
24. Randolph, A. B., & Moore Jackson, M. (2010). Assessing fit of non-traditional assistive technologies. ACM Transactions on Accessible Computing, 2(4). doi: 10.1145/1786774.1786777
25. Randolph, A. B., McCampbell, L. A., Moore, M. M., & Mason, S. G. (2005, July). Controllability of galvanic skin response. Paper presented at the 11th International Conference on Human-Computer Interaction, Las Vegas, NV.
26. Randolph, A. B., Moore Jackson, M., Mason, S. G., & McCampbell, L. A. (2005, June). BioGauges for characterizing biometric interface systems. Paper presented at the Third International Meeting of Brain-Computer Interface Technology, Rensselaerville, NY.
27. Sannelli, C., braun, M., Tangermann, M., & Müller, K.-R. (2008). Estimating noise and dimensionality in BCI data sets: towards bci illiteracy comprehension. Paper presented at the 4th International Brain-Computer Interface Workshop and Training Course, September, Graz, Austria.
28. SAS Institute. (2006). SAS/STAT software: Providing the foundation for SAS' analytic intelligence. Retrieved May 3, 2006, from http://www.sas.com/technologies/analytics/statistics/stat/index.html
29. Schalk, G., McFarland, D. J., Hinterberger, T., Birbaumer, N., & Wolpaw, J. R. (2004). BCI2000: A general-purpose brain-computer interface (BCI) system. IEEE Transactions on Biomedical Engineering, 51, 1034-1043.
30. Tan, L.-F., Jansari, A., Keng, S.-L., & Goh, S.-Y. (2009). Effect of mental training on BCI performance. Paper presented at the 13th International Conference on Human-Computer Interaction, July, San Diego, CA. Part II: Novel Interaction Methods and Techniques.
31. Tran, Y., Boord, P., Middleton, J., & Craig, A. (2004). Levels of brain wave activity (8-13 Hz) in persons with spinal cord injury. Spinal Cord, 42(2), 73-79.
32. Wolpaw, J. R., & Birbaumer, N. (Eds.). (2006). Brain-computer interfaces for communication and control. Cambridge, UK: Cambridge University Press.
33. Wolpaw, J. R., Birbaumer, N., McFarland, D. J., Pfurtscheller, G., & Vaughan, T. M. (2002). Brain-computer interfaces for communication and control. Clinical Neurophysiology, 113, 767-791.
34. Wolpaw, J. R., & McFarland, D. J. (1994). Multichannel EEG-based brain-computer communication. Electroencephalography and Clinical Neurophysiology, 90, 444-449.
35. Wolpaw, J. R., McFarland, D. J., Neat, G. W., & Forneris, C. A. (1991). An EEG-based brain-computer interface for cursor control. Electroencephalography and Clinical Neurophysiology, 78,252-259.