EDP Sciences logo
Subscriber Authentication Point
Search
Menu
Home All issues Volume 31 / No 10 (Octobre 2015) Med Sci (Paris), 31 10 (2015) 904-911 References
Free Access
Issue
Med Sci (Paris)
Volume 31, Number 10, Octobre 2015
Page(s) 904 - 911
Section M/S Revues
DOI https://doi.org/10.1051/medsci/20153110017
Published online 19 October 2015
  1. Posner JP, Saper CB, Schiff ND, Plum F. Plum and Posner’s stupor and coma. New York : Oxford University Press, 2007 : 400 p. [Google Scholar]
  2. 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. [CrossRef] [PubMed] [Google Scholar]
  3. Giacino JT, Ashwal S, Childs N, et al. The minimally conscious state: definition and diagnostic criteria. Neurology 2002 ; 58 : 349–353. [CrossRef] [PubMed] [Google Scholar]
  4. 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. [CrossRef] [PubMed] [Google Scholar]
  5. 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. [CrossRef] [PubMed] [Google Scholar]
  6. Majerus S, Gill-Thwaites H, Andrews K, Laureys S. Behavioral evaluation of consciousness in severe brain damage. Prog Brain Res 2005 ; 150 : 397413. [Google Scholar]
  7. 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. [CrossRef] [PubMed] [Google Scholar]
  8. Lovstad M, Froslie KF, Giacino JT, et al. Reliability and diagnostic characteristics of the JFK coma recovery scale- revised: exploring the influence of rater’s level of experience. J Head Trauma Rehabil 2010 ; 25 : 349–356. [CrossRef] [PubMed] [Google Scholar]
  9. 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. [CrossRef] [PubMed] [Google Scholar]
  10. Thonnard M, Boly M, Bruno MA, et al. La neuro-imagerie : un outil diagnostique des états de conscience altérée. Med Sci (Paris) 2011 ; 27 : 77–81. [CrossRef] [EDP Sciences] [PubMed] [Google Scholar]
  11. Wolpaw JR, Birbaumer N, McFarland DJ, et al. Brain-computer interfaces for communication and control. Clin Neurophysiol 2002 ; 113 : 767–791. [Google Scholar]
  12. 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. [CrossRef] [PubMed] [Google Scholar]
  13. 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. [CrossRef] [PubMed] [Google Scholar]
  14. 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. [Google Scholar]
  15. 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. [CrossRef] [PubMed] [Google Scholar]
  16. Cruse D, Chennu S, Chatelle C, et al. Bedside detection of awareness in the vegetative state. Lancet 2011 ; 378 : 2088–2094. [CrossRef] [PubMed] [Google Scholar]
  17. 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. [CrossRef] [PubMed] [Google Scholar]
  18. 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. [Google Scholar]
  19. 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. [CrossRef] [PubMed] [Google Scholar]
  20. Goldfine 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. [CrossRef] [PubMed] [Google Scholar]
  21. Noirhomme Q, Lesenfants D, Gomez F, et al. Biased binomial assessment of cross-validated estimation of classification accuracies illustrated in diagnosis predictions. Neuroimage Clin 2014 ; 4 : 687–694. [CrossRef] [PubMed] [Google Scholar]
  22. 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. [CrossRef] [Google Scholar]
  23. 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. [CrossRef] [PubMed] [Google Scholar]
  24. 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. [CrossRef] [PubMed] [Google Scholar]
  25. 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. [CrossRef] [PubMed] [Google Scholar]
  26. 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. [CrossRef] [PubMed] [Google Scholar]
  27. 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. [Google Scholar]
  28. Lesenfants D, Habbal D, Chatelle C, et al. An attention-based diagnostic tool for patients with locked-in syndrome. 2015 (soumis pour publication). [Google Scholar]
  29. 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. [CrossRef] [PubMed] [Google Scholar]
  30. Lesenfants D. Interface cerveau-ordinateur, Locked-In syndrome et troubles de la conscience. Doctoral dissertation, Université de Liège, Liège, Belgique, 2014. [Google Scholar]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.