Brain-Computer interfaces for communication: preferences of individuals with locked-in syndrome, caregivers and researchers

References

• Tai K, Blain S, Chau T. A review of emerging access technologies for individuals with severe motor impairments. Assist Technol. 2008;20(4):204–221.
   PubMed Web of Science ®Google Scholar
• Bernat JL. Medical decision making by patients in the locked-in syndrome. Neuroethics. 2020;13(2):229–238.
   Google Scholar
• Brunner C, Birbaumer N, Blankertz B, et al. BNCI horizon 2020: towards a roadmap for the BCI community. Brain-Comput Interfaces. 2015;2(1):1–10.
   Web of Science ®Google Scholar
• Huggins JE, Wren PA, Gruis KL. What would brain-computer interface users want? Opinions and priorities of potential users with amyotrophic lateral sclerosis. Amyotroph Lateral Scler. 2011;12(5):318–324.
   PubMed Web of Science ®Google Scholar
• Basha D, Dostrovsky JO, Lopez Rios AL, et al. Beta oscillatory neurons in the motor thalamus of movement disorder and pain patients. Exp Neurol. 2014;261:782–790.
   PubMed Web of Science ®Google Scholar
• Blain-Moraes S, Schaff R, Gruis KL, et al. Barriers to and mediators of brain-computer interface user acceptance: focus group findings. Ergonomics. 2012;55(5):516–525.
   PubMed 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.
   PubMed Web of Science ®Google Scholar
• Lahr J, Schwartz C, Heimbach B, et al. Invasive brain-machine interfaces: a survey of paralyzed patients’ attitudes, knowledge and methods of information retrieval. J Neural Eng. 2015;12(4):043001.
   PubMed Web of Science ®Google Scholar
• Blabe CH, Gilja V, Chestek CA, et al. Assessment of brain-machine interfaces from the perspective of people with paralysis. J Neural Eng. 2015;12(4):043002.
   PubMed Web of Science ®Google Scholar
• Huggins JE, Moinuddin AA, Chiodo AE, et al. What would Brain-Computer interface users want: opinions and priorities of potential users with spinal cord injury. Arch Phys Med Rehabil. 2015;96(3):S38–S45.e5.
   PubMed Web of Science ®Google Scholar
• Fager SK, Fried-Oken M, Jakobs T, et al. New and emerging access technologies for adults with complex communication needs and severe motor impairments: State of the science. Augment Altern Commun. 2019;35(1):13–13.
   PubMed Web of Science ®Google Scholar
• Andresen EM, Fried-Oken M, Peters B, et al. Initial constructs for patient-centered outcome measures to evaluate brain-computer interfaces. Disabil Rehabil Assist Technol. 2016;11(7):548–557.
   PubMed Web of Science ®Google Scholar
• Nijboer F, Bos DP-O, Blokland Y, et al. Design requirements and potential target users for brain-computer interfaces – recommendations from rehabilitation professionals. Brain-Comput Interfaces. 2014;1(1):50–61.
   Google Scholar
• Branco MP, Pels EGM, Sars RH, et al. Brain-computer interfaces for communication: Preferences of individuals with locked-in syndrome. Neurorehabil Neural Repair. 2021;35(3):267–279. Published online February 3, 1545968321989331.
   PubMed Web of Science ®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.
   PubMed Web of Science ®Google Scholar
• Zickler C, Halder S, Kleih SC, 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.
   PubMed Web of Science ®Google Scholar
• Botrel L, Holz EM, Kübler A. Brain painting V2: evaluation of P300-based brain-computer interface for creative expression by an end-user following the user-centered design. Brain-Comput Interfaces. 2015;2(2–3):135–149.
   Web of Science ®Google Scholar
• Holz EM, Botrel L, Kübler A. Independent home use of brain painting improves quality of life of two artists in the locked-in state diagnosed with amyotrophic lateral sclerosis. Brain-Comput Interfaces. 2015;2(2–3):117–134.
   Web of Science ®Google Scholar
• Botrel L, Holz EM, Kübler A. Using brain painting at home for 5 years: stability of the P300 during prolonged BCI usage by two End-Users with ALS. In: International Conference on Augmented Cognition. Cham: Springer; 2017. p. 282–292.
   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? Prog Brain Res. 2005;150:495–511. DOI:10.1016/S0079-6123(05)50034
   Google Scholar
• Kübler A, Nijboer F, Mellinger J, et al. Patients with ALS can use sensorimotor rhythms to operate a brain-computer interface. Neurology. 2005;64(10):1775–1777.
   PubMed Web of Science ®Google Scholar
• Bruno M-A, Bernheim JL, Ledoux D, et al. A survey on self-assessed well-being in a cohort of chronic locked-in syndrome patients: happy majority, miserable minority. BMJ Open. 2011;1(1):e000039.
   PubMed Web of Science ®Google Scholar
• Rousseau M-C, Baumstarck K, Alessandrini M, et al. Quality of life in patients with locked-in syndrome: evolution over a 6-year period. Orphanet J Rare Dis. 2015;10:88.
   PubMed Web of Science ®Google Scholar
• Sellers EW, Donchin E. A P300-based brain-computer interface: initial tests by ALS patients. Clin Neurophysiol. 2006;117(3):538–548.
   PubMed Web of Science ®Google Scholar
• Kübler Furdea A, Halder S, Hammer EM, et al. A brain-computer interface controlled auditory event-related potential (p300) spelling system for locked-in patients. Ann N Y Acad Sci. 2009;1157(1):90–100.
   PubMedGoogle Scholar
• Pires G, Nunes U, Castelo-Branco M. Statistical spatial filtering for a P300-based BCI: Tests in able-bodied, and patients with cerebral palsy and amyotrophic lateral sclerosis. J Neurosci Methods. 2011;195(2):270–281.
   PubMed Web of Science ®Google Scholar
• Brunner P, Ritaccio AL, Emrich JF, et al. Rapid communication with a “P300” matrix speller using electrocorticographic signals (ECoG). Front Neurosci. 2011;5:5.
   PubMed Web of Science ®Google Scholar
• Vansteensel MJ, Kristo G, Aarnoutse EJ, et al. The brain-computer interface researcher’s questionnaire: from research to application. Brain-Comput Interfaces. 2017;4(4):236–247.
   Web of Science ®Google Scholar
• Wolpaw JR, Bedlack RS, Reda DJ, et al. Independent home use of a brain-computer interface by people with amyotrophic lateral sclerosis. Neurology. 2018;91(3):e258–e267.
   PubMed Web of Science ®Google Scholar
• Parker SM, Clayton JM, Hancock K, et al. A systematic review of prognostic/end-of-life communication with adults in the advanced stages of a life-limiting illness: patient/caregiver preferences for the content, style, and timing of information. J Pain Symptom Manage. 2007;34(1):81–93.
   PubMed Web of Science ®Google Scholar
• Hancock K, Clayton JM, Parker SM, et al. Discrepant perceptions about end-of-Life communication: a systematic review. J Pain Symptom Manage. 2007;34(2):190–200.
   PubMed Web of Science ®Google Scholar
• Hogden A, Greenfield D, Nugus P, et al. Engaging in patient decision-making in multidisciplinary care for amyotrophic lateral sclerosis: the views of health professionals. Patient Prefer Adherence. 2012;6:691–701.
   PubMed Web of Science ®Google Scholar
• Versalovic E, Diamond M, Klein E. “Re-identifying yourself”: a qualitative study of veteran views on implantable BCI for mobility and communication in ALS. Disabil Rehabil Assist Technol. 2020;17:1–8.
   PubMed Web of Science ®Google Scholar
• Ahmed E, Alike Q, Keselman A. The process of creating online animated videos to overcome literacy barriers in health information outreach. J Consum Health Internet. 2015;19(3–4):184–199.
   Web of Science ®Google Scholar
• Johnston P, Currie LM, Drynan D, et al. Getting it “right”: how collaborative relationships between people with disabilities and professionals can lead to the acquisition of needed assistive technology. Disabil Rehabil Assist Technol. 2014;9(5):421–431.
   PubMedGoogle Scholar