Interfaces cerveau-ordinateur, locked-in syndrome et troubles de la conscience.

[en] Detecting signs of consciousness in patients with severe brain injury constitutes a real challenge for clinicians. The current gold standard in clinical diagnosis is the behavioral scale relying on motor abilities, which are often impaired or nonexistent in these patients. In this context, brain-computer interfaces (BCIs) could offer a potential complementary tool to detect signs of consciousness whilst bypassing the usual motor pathway. In addition to complementing behavioral assessments and potentially reducing error rate, BCIs could also serve as a communication tool for paralyzed but conscious patients, e.g., suffering from Locked-In Syndrome. In this paper, we report on recent work conducted by the Coma Science Group on BCI technology, aiming to optimize diagnosis and communication in patients with disorders of consciousness and Locked-In syndrome.

Disciplines :

Neurology

Author, co-author :

Lesenfants, Damien

Chatelle, Camille ; Université de Liège - ULiège

Laureys, Steven ; Université de Liège > GIGA : Coma Group

Noirhomme, Quentin ; Université de Liège > Centre de recherches du cyclotron

Language :

French

Title :

Interfaces cerveau-ordinateur, locked-in syndrome et troubles de la conscience.

Alternative titles :

[en] Brain-computer interfaces, Locked-In syndrome, and disorders of consciousness

Publication date :

2015

Journal title :

MS. Medecine Sciences

ISSN :

0767-0974

eISSN :

1958-5381

Publisher :

Editions EDK, France

Volume :

Issue :

Pages :

904-11

Commentary :

Available on ORBi :

since 22 January 2016

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Bibliography

Posner JP, Saper CB, Schiff ND, Plum F. Plum and Posner's stupor and coma. New York: Oxford University Press, 2007: 400 p.
Bruno MA, Vanhaudenhuyse A, Thibaut A, et al. From unresponsive wakefulness to minimally conscious plus and functional locked-in syndromes: recent advances in our understanding of disorders of consciousness. J Neurol 2011; 258: 1373-1384.
Giacino JT, Ashwal S, Childs N, et al. The minimally conscious state: deffinition and diagnostic criteria. Neurology 2002; 58: 349-353.
Bruno MA, Majerus S, Boly M, et al. Functional neuroanatomy underlying the clinical subcate-gorization of minimally conscious state patients. J Neurol 2011; 259: 1087-1098.
Laureys S, Perrin F, Schnakers C, et al. Residual cognitive function in comatose, vegetative and minimally conscious states. Curr Opin Neurol 2005; 18: 726-733.
Majerus S, Gill-Thwaites H, Andrews K, Laureys S. Behavioral evaluation of consciousness in severe brain damage. Prog Brain Res 2005; 150: 397413.
Majerus S, Bruno MA, Schnakers C, et al. The problem of aphasia in the assessment of consciousness in brain-damaged patients. Prog Brain Res 2009; 177: 49-61.
Lovstad M, Froslie KF, Giacino JT, et al. Reliability and diagnostic characteristics of the JFK coma recovery scale-revised: exploring the in? uence of rater's level of experience. J Head Trauma Rehabil 2010; 25: 349-356.
Schnakers C, Vanhaudenhuyse A, Giacino JT, et al. Diagnostic accuracy of the vegetative and minimally conscious state: clinical consensus versus standardized neuro-behavioral assessment. BMC Neurol 2009; 9: 35.
Thonnard M, Boly M, Bruno MA, et al. La neuro-imagerie: un outil diagnostique des états de conscience altéreé. Med Sci (Paris) 2011; 27: 77-81.
Wolpaw JR, Birbaumer N, McFarland DJ, et al. Brain-computer interfaces for communication and control. Clin Neurophysiol 2002; 113: 767-791.
Boly M, Coleman MR, Hampshire A, et al. When thoughts become action: an fmri paradigm to study volitional brain activity in non-communicative brain injured patients. Neuroimage 2007; 36: 979-992.
Monti MM, Vanhaudenhuyse A, Coleman MR, et al. Willful modulation of brain activity in disorders of consciousness. N Engl J Med 2010; 362: 579-589.
Chatelle C, Lesenfants D, Guller Y, et al. BCI for assessing consciousness in severely brain-injured patients. In: Rossetti AO, Laureys S, eds. Clinical neurophysiology in disorders of consciousness. Wien: Springer-Verlag, 2015: 133-148.
Birbaumer N, Kübler A, Ghanayim N, et al. The thought translation device (TTD) for completely paralyzed patients. IEEE Trans Rehabil Eng 2000; 8: 190-193.
Cruse D, Chennu S, Chatelle C, et al. Bedside detection of awareness in the vegetative state. Lancet 2011; 378: 2088-2094.
Pokorny C, Klobassa DS, Pichler G, et al. The auditory p300-based single-switch brain-computer interface: paradigm transition from healthy subjects to minimally conscious patients. Artif Intell Med 2013; 59: 81-90.
Middendorf M, McMillan G, Calhoun G, Jones KS. Brain-computer interfaces based on the steady-state visual-evoked response. IEEE Trans Rehabil Eng 2000; 8: 211-214.
Lesenfants D, Habbal D, Lugo ZR, et al. An independent SSVEP-based brain-computer interface in locked-in syndrome. J Neural Eng 2014; 11: 035002.
Goldne AM, Bardin JC, Noirhomme Q, et al, Reanalysis of bedside detection of awareness in the vegetative state: a cohort study. Lancet, 2013, 381, 289-291.
Noirhomme Q, Lesenfants D, Gomez F, et al. Biased binomial assessment of cross-validated estimation of classi? cation accuracies illustrated in diagnosis predictions. Neuroimage Clin 2014; 4: 687-694.
Bin G, Gao X, Yan Z, et al. An online multi-channel SSVEP-based brain-computer interface using a canonical correlation analysis method. J Neural Eng 2009; 6: 46002-46008.
Müller-Putz GR, Scherer R, Brauneis C, Pfurtscheller G. Steady-state visual evoked potential (SSVEP) based communication: impact of harmonic frequency components. J Neural Eng 2005; 2: 123-130.
Allison BZ, McFarland DJ, Schalk G, et al. Towards an independent brain-computer interface using steady state visual evoked potentials. Clin Neurophysiol 2008; 119: 399-408.
Kelly SP, Lalor EC, Finucane C, et al. Visual spatial attention control in an independent brain-computer interface. IEEE Trans Biomed Eng 2005; 52: 1588-1596.
Zhang D, Maye A, Gao X, et al. An independent brain-computer interface using covert non-spatial visual selective attention. J Neural Eng 2010; 7: 16010-16021.
Lesenfants D, Partoune N, Soddu A, et al. Design of a novel covert SSVEP-based BCI. Proceedings 5th International Brain-Computer Interface Conference. Graz, Austria, 2011.
Lesenfants D, Habbal D, Chatelle C, et al. An attention-based diagnostic tool for patients with locked-in syndrome. 2015 (soumis pour publication).
Viertio-Oja H, Maja V, Sarkela M, et al. Description of the entropyTM algorithm as applied in the datex-ohmeda S/5TM entropy module. Acta Anaesthesiol Scand 2004; 48: 154-161.
Lesenfants D. Interface cerveau-ordinateur, Locked-In syndrome et troubles de la conscience. Doctoral dissertation, Université de Liège, Liège, Belgique, 2014.