Abstract
Patients diagnosed with complete locked in syndrome (CLIS) or a disorder of consciousness (DOC) have no reliable control of voluntary movements. Hence, assessing their cognitive functions and cognitive awareness can be challenging. The “gold standard” for such assessments relies on behavioral responses, and recent work using different neuroimaging methods has shown that behavioral diagnoses may underestimate patients’ capabilities. Thus, there is a pressing need for new methods that go beyond behavioral approaches and can help patients even if they are not able to produce any behavioral response. In one of the most prominent trends in brain-computer interface (BCI) research, many groups have been using BCI technology to provide a suite of approaches to assess cognition and consciousness using EEG-based tools. This paper presents results with P300, steady-state visual evoked potential (SSVEP) and motor imagery BCIs and other approaches with different target patients in several different real-world settings. Results confirm that EEG-based assessment can reveal details about patients’ remaining capabilities that can both change and extend diagnoses based on behavioral measures. The results can already be used in clinical practice to help physicians, patients, and families develop a more detailed and accurate assessments, and provide hope for further technical and methodological improvements through future research.
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References
Guger C, Noirhomme Q, Naci L, Real R, Lugo Z, Veser S, Sorger B, Quitadamo L, Lesenfants D, Risetti M, Formisano R, Toppi J, Astolfi L, Emmerling T, Erlbeck H, Monti MM, Kotchoubey B, Bianchi L, Mattia D, Goebel R, Owen AM, Pellas F, Müller-Putz G, Kübler A (2014) Brain-computer interfaces for coma assessment and communication. In: Ganesh RN (ed) Emerging theory and practice in neuroprosthetics. IGIGLOBAL Press
Lesenfants D, Habbal D, Chatelle C, Schnakers C, Laureys S, Noirhomme Q Electromyographic decoding of response to command in disorders of consciousness, submitted A
Coyle D, Stow J, McCreadie K, Sciacca N, McElligott J, Carroll Á (2017) Motor imagery BCI with auditory feedback as a mechanism for assessment and communication in disorders of consciousness. In: Brain-Computer Interface Research. Springer International Publishing, pp 51–69
Laureys S, Pellas F, Van Eeckhout P, Ghorbel S, Schnakers C, Perrin F, Berre J, Feymonville ME, Pantke KH, Damas F, Lamy M, Moonen G, Goldman S (2005) The locked-in syndrome: What is it like to be conscious but paralyzed and voiceless? Prog Brain Res 150:495–511
Ortner R, Lugo Z, Prückl R, Hintermüller C, Noirhomme Q, Guger C (2013) Performance of a tactile P300 speller for healthy people and severely disabled patients. In: Proceedings of the 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC 2013), Osaka, JP. 3–7 July 2013
Lugo ZR, Rodriguez J, Lechner A, Ortner R, Gantne IS, Laureys S, Guger C (2014) A vibrotactile p 300-based brain-computer interface for consciousness detection and communication. Clin EEG Neurosci 45:14–21
Guger C, Kapeller C, Ortner R, Kamada K (2015) Motor imagery with brain-computer interface neurotechnology. In: Garcia BM (ed) Motor imagery: emerging practices, role in physical therapy and clinical implications, pp 61–79
Guger C, Spataro R, Allison BZ, Heilinger A, Ortner R, Cho W, La Bella V (2017) Complete locked-in and locked-in patients: command following assessment and communication with vibro-tactile P300 and motor imagery brain-computer interface tools. Front Neurosci 11
Coyle D et al (2012) Enabling control in the minimally conscious state in a single session with a three channel BCI. In: 1st International Decoder Workshop, April, pp 1–4
Coyle D et al (2015) Sensorimotor modulation assessment and brain-computer interface training in disorders of consciousness. Arch Phys Med Rehabil 96(3):62–70
Coyle D et al (2013) Visual and stereo audio sensorimotor rhythm feedback in the minimally conscious state. In: Proceedings of the Fifth International Brain-Computer Interface Meeting 2013, pp 38–39
Cruse D, Chennu S, Chatelle C, Bekinschtein TA, Fernández-Espejo D, Pickard JD, Owen AM (2011) Bedside detection of awareness in the vegetative state: a cohort study. Lancet 378(9809):2088–2094
Nuffield Council on Bioethics Report (2013) Novel neurotechnologies : intervening in the brain. http://nuffieldbioethics.org/wp-content/uploads/2013/06/Novel_neurotechnologies_report_PDF_web_0.pdf
Aricò P, Aloise F, Schettini F, Salinari S, Mattia D, Cincotti F (2014) Influence of P300 latency jitter on event related potential-based brain-computer interface performance. J Neural Eng 11(3):035008
Schettini F, Risetti M, Arico P, Formisano F, Babiloni F, Mattia D, Cincotti F (2015) P300 latency Jitter occurrence in patients with disorders of consciousness: toward a better design for brain computer interface applications. In: Engineering in Medicine and Biology Society (EMBC), 2015 37th Annual International Conference of the IEEE, 2015, pp 6178–6181
Olsson C-J, Nyberg L (2010) Motor imagery: If you can’t do it, you won’t think it. Scand J Med Sci Sports 20:711–715
Bovend’Eerdt TJH, Dawes H, Sackley C, Wade DT (2012) Practical research-based guidance for motor imagery practice in neurorehabilitation. Disabil Rehabil 34(25):2192–2200
Snyder AZ (1992) Steady-state vibration evoked potentials: description of technique and characterization of responses. Electroencephalogr Clin Neurophysiol Potentials Sect 84(3):257–268
Severens M, Farquhar J, Duysens J, Desain P (2013) A multi-signature brain-computer interface: use of transient and steady-state responses. J Neural Eng 10(2):026005
Choi I, Bond K, Krusienski D, Nam CS (2015) Comparison of stimulation patterns to elicit steady-state somatosensory evoked potentials (SSSEPs): implications for hybrid and SSSEP-based BCIs. In: IEEE International Conference on Systems, Man, and Cybernetics (SMC), 2015
Giacino JT, Kalmar K, Whyte J (2004) The JFK Coma Recovery Scale-Revised: Measurement characteristics and diagnostic utility. Arch Phys Med Rehabil 85(12):2020–2029
Laureys S, Perrin F, Faymonville M-E, Schnakers C, Boly M (2004) Cerebral processing in the minimally conscious state. Neurology 63:916–918
Jox RJ, Bernat JL, Laureys S, Racine E (2012) Disorders of consciousness: responding to requests for novel diagnostic and therapeutic interventions. Lancet Neurol 11(8):732–738
Bruno MA, Bernheim JL, Ledoux D, Pellas F, Demertzi A, Laureys S (2011) A survey on self assessed well-being in a cohort of chronic locked-in syndrome patients: happy majority, miserable minority. BMJ Open 1(1):1–9
Bekinschtein TA, Coleman MR, Niklison J, Pickard JD, Manes FF (2008) Can electromyography objectively detect voluntary movement in disorders of consciousness? J Neurol Neurosurg Psychiatry 79(7):826–828
Habbal D, Gosseries O, Noirhomme Q, Renaux J, Lesenfants D, Bekinschtein TA, Majerus S, Laureys S, Schnakers C (2014) Volitional electromyographic responses in disorders of consciousness. Brain Inj 28(9):1171–1179
Stoll J, Chatelle C, Carter O, Koch C, Laureys S, Einhäuser W (2013) Pupil responses allow communication in locked-in syndrome patients. Curr Biol 23(15):R647–R648
Ruf CA, DeMassari D, Wagner-Podmaniczky F, Matuz T, Birbaumer N (2013) Semantic conditioning of salivary pH for communication. Artif Intell Med 59(2):91–98
Wilhelm B, Jordan M, Birbaumer N (2006) Communication in locked-in syndrome: effects of imagery on salivary pH. Neurology 67(3):534–535
Charland-Verville V, Lesenfants D, Sela L, Noirhomme Q, Ziegler E, Chatelle C, Plotkin A, Sobel N, Laureys S (2014) Detection of response to command using voluntary control of breathing in disorders of consciousness. Front Hum Neurosci 8
Laureys S, Schiff ND (2012) Coma and consciousness: paradigms (re)framed by neuroimaging. NeuroImage 61:1681–1691
Acknowledgements
The work of g.tec was supported by the H2020 grant ComaWare and ComAlert (project number E! 9361 Com-Alert). Q. Noirhomme has received funding from the European Community’s Seventh Framework Program under grant agreement n° 602450 (IMAGEMEND). Research at OHSU was supported by NIH grant R01DC014294 and NIDILRR grant 90RE5017. Research at MGH was supported by NIH grant K23NS094538 and the American Academy of Neurology/American Brain Foundation. Research at NCSU was supported by NSF grant IIS1421948. Marzia De Lucia’s research at Lausanne University Hospital is supported by the “EUREKA-Eurostars” grant (project number E! 9361 Com-Alert). The work was partially supported by the Italian Ministry of Healthcare and the French Speaking Community Concerted Research Action (ARC-06/11-340). This paper reflects only the authors’ view and the funding sources are not liable for any use that may be made of the information contained therein.
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Guger, C. et al. (2017). Trends in BCI Research I: Brain-Computer Interfaces for Assessment of Patients with Locked-in Syndrome or Disorders of Consciousness. In: Guger, C., Allison, B., Lebedev, M. (eds) Brain-Computer Interface Research. SpringerBriefs in Electrical and Computer Engineering. Springer, Cham. https://doi.org/10.1007/978-3-319-64373-1_11
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DOI: https://doi.org/10.1007/978-3-319-64373-1_11
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