Immobilis in mobili: performing arts, BCI, and locked-in syndrome

References

• Biskjaer MM, Dalsgaard P, Halskov K. Creativity methods in interaction design. In: Proceedings of the 1st DESIRE Network Conference on Creativity and Innovation in Design; 2010.
   Google Scholar
• Candy L. Constraints and creativity in the digital arts. Leonardo. 2005;40(4):366–367.
   Web of Science ®Google Scholar
• Laureys S, Pellas F, Van Eeckhout P, et al. The locked-in syndrome: what is it like to be conscious but paralyzed and voiceless? In: Laureys S, editor. The boundaries of consciousness: Neurobiology and Neuropathology. Amsterdam; Elsevier; 2005. p. 495–611.
   Google Scholar
• Majaranta P, Räihä KJ. Twenty years of eye typing: systems and design issues. In: Proceedings of the 2002 symposium on Eye tracking research & applications, ETRA ‘02; New York, (USA); 2002.
   Google Scholar
• Riveros R, García C, Aparicio A, et al. Tecnología, acompañamiento psicológico y neuropsicología: tres vías para salir del síndrome de enclaustramiento. [Technology, psychological support and neuropsychology: three ways to unlock locked-in syndrome]. Revista Chilena de Neuropsicología. 2014;9(1): 14–20. Spanish.
   Google Scholar
• Neuper C, Muller GR, Kübler A, et al. Clinical application of an EEG-based brain-computer interface: a case study in a patient with severe motor impairment. Clin Neurophysiol. 2003;114(3):399–409.10.1016/S1388-2457(02)00387-5
   PubMed Web of Science ®Google Scholar
• Halder S, Ruf CA, Furdea A, et al. Prediction of P300 BCI aptitude in severe motor impairment. PLoS ONE. 2013;8(10):e76148.10.1371/journal.pone.0076148
   Google Scholar
• Amiri S, Rabbi A, Azinfar L, et al. A review of P300, SSVEP, and hybrid P300/SSVEP brain-computer interface systems. In: Fazel-Rezai F, editor. Brain-Computer Interface Systems – Recent Progress and Future Prospects. InTech; 2013. p. 195–213.
   Google Scholar
• Höhne J, Holz E, Staiger-Sälzer P, et al. Motor imagery for severely motor-impaired patients: evidence for brain-computer interfacing as superior control solution. PLoS ONE. 2014;9(8):e104854.10.1371/journal.pone.0104854
   PubMed Web of Science ®Google Scholar
• Sellers EW, Vaughan TM, Wolpaw JR. A brain-computer interface for long-term independent home use. Amyotroph Lateral Scler. 2010 Oct;11(5):449–455. doi:10.3109/17482961003777470.
   PubMed Web of Science ®Google Scholar
• Zickler C, Riccio A, Leotta F, Hillian-Tress S, Halder S, Holz E, Staiger-Sälzer P, Hoogerwerf EJ, Desideri D, Mattia D, Kübler A. A brain-computer interface as input channel for a standard assistive technology software. Clin EEG Neurosci. 2011 Oct;42(4):236–244.
   PubMed Web of Science ®Google Scholar
• Holz EM, Botrel L, Kaufmann T, Kübler, A. 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. 2015 Mar;96 (3 Suppl):S16–26. doi:10.1016/j.apmr.2014.03.035.
   Web of Science ®Google Scholar
• Clarke A, Mitchell G, editors. Videogames and art. Bristol; Intellect books; 2007.
   Google Scholar
• Aparicio A. The locked-in playwright: the importance of user interaction models in technology-assisted intervention. Poster session presented at: Annual Meeting of the American Academy of Clinical Neuropsychology; 2014; New York, NY.
   Google Scholar
• Hornof AJ, Cavender A. EyeDraw: enabling children with severe motor impairments to draw with their eyes. In: Proceedings of the SIGCHI conference on Human factors in computing systems; 2005.
   Google Scholar
• Hornof AJ, Rogers T, Halverson T. EyeMusic: performing live music and multimedia compositions with eye movements. In: Proceedings of the 7th international conference on New interfaces for musical expression; 2007.
   Google Scholar
• Münßinger JI, Halder S, Kleih SC, et al. Brain painting: first evaluation of a new brain–computer interface application with ALS-patients and healthy volunteers. Front Neurosci. 2010;4(182):1–11.
   PubMedGoogle Scholar
• Miranda ER. Brain-computer music interface for composition and performance. Int J Disabil Hum Dev. 2006;5(2):119–126. doi:10.1515/IJDHD.2006.5.2.119.
   Google Scholar
• Miranda ER, et al. Brain-computer music interfacing (BCMI) from basic research to the real world of special needs. Music and Medicine. 2011;3(3):134–140. doi:10.1177/1943862111399290.
   Google Scholar
• Migotina D, Isidoro C, Rosa A. Brain art: abstract visualization of sleeping brain. Paper presented at: 14th generative art conference GA2011; 2011.
   Google Scholar
• De Smedt T, Menschaert L. VALENCE: affective visualisation using EEG. Digital Creativity. 2012;23(3–4):272–277.10.1080/14626268.2012.719240
   Web of Science ®Google Scholar
• Kochhar-Lindgren K. Hearing difference across theatres: experimental, disability, and deaf performance. Theat J. 2006;58(3):417–436.10.1353/tj.2006.0159
   Web of Science ®Google Scholar
• Sandahl C. Considering disability: Disability phenomenology’s role in revolutionizing theatrical space. J Drama Theory Crit. 2002;2:17–32.
   Google Scholar
• Fox AM, Lipkin J. Res (crip) ting feminist theater through disability theater: Selections from the DisAbility Project. NWSA J. 2002;14(3):77–98.10.2979/nws.2002.14.issue-3
   Google Scholar
• Sandahl C. Why disability identity matters: from dramaturgy to casting in John Belluso’s Pyretown. Text Perform Quart. 2008;28(1–2):225–241.10.1080/10462930701754481
   Web of Science ®Google Scholar
• WHO: Health Topics: Disabilities [Internet]. World Health Organization; 2015 Mar 28 [ cited 2015 Mar 30]; [ about 1 screen]. Available from: http://www.who.int/topics/disabilities/en/
   Google Scholar
• Galanter P. What is Generative Art? Complexity theory as a context for art theory. In: GA2003–6th Generative Art Conference; 2003.
   Google Scholar
• Dannenberg RB, Bates J. A model for interactive art. In: Proceedings of the Fifth Biennial Symposium for Arts and Technology; 1995.
   Google Scholar
• Pearson KA. Life becoming body: on the ‘meaning’of post human evolution. J Cultural Res. 1997;1(2):219–240. doi:10.1080/14797589709367145.
   Google Scholar
• Stelarc. The Cadaver, The Comatose & The Chimera: Alternate Anatomical Architectures. Amber’09 Arts and Technology Festival [ Internet]; 2009 Nov [Cited on 2015 Aug0 24]; [ 9 pages]. Available from: http://stelarc.org/documents/StelarcLecture2009.pdf
   Google Scholar
• Wilde D, Schiphorst T, Klooster S. Move to Design • Design to Move: a conversation about designing for the body. interactions. 2011;18(4):22–27.10.1145/1978822
   Google Scholar
• Wilde D. Extending body & imagination: moving to move. Int J Disabil Hum Dev. 2011;10(1):31–36.
   Google Scholar
• Buller T. Neurotechnology, Invasiveness and the Extended Mind. Neuroethics. 2013;6(3):593–605. doi:10.1007/s12152-011-9133-5.
   Web of Science ®Google Scholar
• Schicktanz S, Amelung T, Rieger JW. Qualitative assessment of patients’ attitudes and expectations toward BCIs and implications for future technology development. Front Syst Neurosci. 2015;9:64. doi:10.3389/fnsys.2015.00064.
   PubMed Web of Science ®Google Scholar
• Zander T, Kothe C. Towards passive brain-computer interfaces: applying brain-computer interface technology to human-machine systems in general. J Neural Eng. 2011;8(2):025005.10.1088/1741-2560/8/2/025005
   PubMed Web of Science ®Google Scholar
• Krauledat M, Tangermann M, Blankertz B, et al. Towards zero training for brain-computer interfacing. PLoS ONE. 2008;3(8):e2967. doi:10.1371/journal.pone.0002967.
   Google Scholar
• Cecotti H. A self-paced and calibration-less SSVEP-based brain–computer interface speller. IEEE Trans Neural Syst Rehabil Eng. 2010;18(2):127–133. doi:10.1109/TNSRE.2009.2039594.
   PubMed Web of Science ®Google Scholar
• Kindermans P-J, Verstraeten D, Schrauwen B. A Bayesian model for exploiting application constraints to enable unsupervised training of a P300-based BCI. PLoS ONE. 2012;7(4):e33758. doi:10.1371/journal.pone.0033758.
   PubMed Web of Science ®Google Scholar
• Kindermans P-J, Schreuder M, Schrauwen B, et al. True zero-training brain-computer interfacing – An online study. PLoS ONE. 2012;9(7):e102504. doi:10.1371/journal.pone.0102504.
   Google Scholar
• Iturrate I, Grizou J, Omedes J, et al. Exploiting task constraints for self-calibrated brain-machine interface control using error-related potentials. PLoS ONE. 2015;10(7):e0131491. doi:10.1371/journal.pone.0131491.
   PubMed Web of Science ®Google Scholar
• Guger C, Daban S, Sellers E, Holzner C, Krausz G, Carabalona R, Gramatica F, Edlinger G. How many people are able to control a P300-based brain-computer interface (BCI)? Neurosci Lett. 2009 Oct 2;462(1):94–98. doi:10.1016/j.neulet.2009.06.045.
   Google Scholar
• Guger, et al. How many people are able to control a P300-based brain-computer interface (BCI)? Front Neurosci. 2012;6:169. doi:10.3389/fnins.2012.00169.
   PubMed Web of Science ®Google Scholar
• Zickler C, Halder S, Kleih S-C, et al. Brain painting: usability testing according to the user-centered design in end users with severe motor paralysis. Artif Intell Med. 2013;59(2):99–110. doi:10.1016/j.artmed.2013.08.003.
   PubMed Web of Science ®Google Scholar
• Kübler. The user-centered design as novel perspective for evaluating the usability of BCI-controlled applications. PLoS ONE. 2013;9(12):e112392. doi:10.1371/journal.pone.0112392.
   Google Scholar
• Fazel-Rezai R, Allison BZ, Guger C, et al. P300 brain computer interface: current challenges and emerging trends. Front Neuroeng. 2012;5.
   Google Scholar
• Klonowski et al., Some computational aspects of the brain computer interfaces based on inner music. Comput Intell Neurosci. 2009:950403. doi:10.1155/2009/950403.
   Google Scholar
• Stelarc. Zombies & Cyborgs [ Internet]. Stelarc website; [cited 2015 Aug 24]; [about 10 pages]. Available from: http://stelarc.org/documents/zombiesandcyborgs.pdf
   Google Scholar
• Mullen T, Warp R, Jansch A. Minding the (transatlantic) gap: an internet-enabled acoustic brain-computer music interface. In Proceedings of the International Conference on New Interfaces for Musical Expression. 2011 May;30:469–472. Available from: http://www.nime.org/proceedings/2011/nime2011_469.pdf
   Google Scholar