Abstract
Facebrain is a novel brain-computer interface utilizing the P300 signal as input for interacting with the Facebook social media platform. Electroencephalography along with the open-source BCI2000 software suite is used for both obtaining and processing the signals. Additionally, BCPy2000, an add-on allowing BCI2000 modules to be written in the scripting language Python, is utilized to allow for rapid interface generation, promoting extensibility, and a cross-platform solution. Users are able to select basic Facebook operations via a P300 matrix and then activate a P300 speller as needed for text input. Overall, the purpose of the system is to allow functional, hands-free, and voiceless access to Facebook’s main features including, but not limited to, searching for and adding friends, making posts, using the chat system, and browsing profiles.
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References
Vance, A.: Facebook: The Making of 1 Billion Users. Bloomberg Businessweek (2012)
Nijholt, A., et al.: Brain-computer interfacing for intelligent systems. IEEE Intell. Syst. 23(3), 72–79 (2008)
Wolpaw, J.R., et al.: Brain-computer interfaces for communication and control. Clin. Neurophysiol. 113(6), 767–791 (2002)
Randolph, A.B., Moore, M.M.: Jackson, assessing fit of nontraditional assistive technologies. ACM Trans. Accessible Comput. 2(4), 1–31 (2010)
Holz, E.M., et al.: Long-term independent brain-computer interface home use improves quality of life of a patient in the locked-in state: a case study. Arch. Phys. Med. Rehabil. 96(3), S16–S26 (2015)
Moore, M.M.: Real-world applications for brain-computer interface technology. IEEE Trans. Neural Syst. Rehabil. Eng. 11(2), 162–165 (2003)
Halder, S., et al.: Brain-controlled applications using dynamic P300 speller matrices. Artif. Intell. Med. 63(1), 7–17 (2015)
Kübler, A., et al.: A brain-computer interface controlled auditory event-related potential (p300) spelling system for locked-in patients. Ann. N. Y. Acad. Sci. 1157, 90–100 (2009)
Pinegger, A., et al.: Control or non-control state: that is the question! An asynchronous visual P300-based BCI approach. J. Neural Eng. 12(1), 014001 (2015)
Schalk, G., et al.: BCI2000: a general-purpose brain-computer interface (BCI) system. IEEE Trans. Biomed. Eng. 51(6), 1034–1043 (2004)
Schalk, G.: Effective brain-computer interfacing using BCI2000. In: IEEE Engineering in Medicine and Biology Society (2009)
Aarts, H., Verplanken, B., Van Knippenberg, A.: Predicting behavior from actions in the past: repeated decision making or a matter of habit. J. Appl. Soc. Psychol. 28(15), 1355–1374 (1998)
Farwell, L.A., Donchin, E.: Talking off the top of your head: toward a mental prothesis utilizing event-related brain potentials. Electroencephalogr. Clin. Neurophysiol. 70(6), 510–523 (1988)
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Warren, B., Randolph, A.B. (2019). Facebrain: A P300 BCI to Facebook. In: Davis, F., Riedl, R., vom Brocke, J., Léger, PM., Randolph, A. (eds) Information Systems and Neuroscience. Lecture Notes in Information Systems and Organisation, vol 29. Springer, Cham. https://doi.org/10.1007/978-3-030-01087-4_14
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DOI: https://doi.org/10.1007/978-3-030-01087-4_14
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