[en] Objective: Within this work an auditory P300 brain–computer interface based on tone stream segregation,which allows for binary decisions, was developed and evaluated.Methods and materials: Two tone streams consisting of short beep tones with infrequently appearingdeviant tones at random positions were used as stimuli. This paradigm was evaluated in 10 healthysubjects and applied to 12 patients in a minimally conscious state (MCS) at clinics in Graz, Würzburg,Rome, and Liège. A stepwise linear discriminant analysis classifier with 10 × 10 cross-validation was usedto detect the presence of any P300 and to investigate attentional modulation of the P300 amplitude.Results: The results for healthy subjects were promising and most classification results were better thanrandom. In 8 of the 10 subjects, focused attention on at least one of the tone streams could be detectedon a single-trial basis. By averaging 10 data segments, classification accuracies up to 90.6 % could bereached. However, for MCS patients only a small number of classification results were above chance leveland none of the results were sufficient for communication purposes. Nevertheless, signs of consciousnesswere detected in 9 of the 12 patients, not on a single-trial basis, but after averaging of all correspondingdata segments and computing significant differences. These significant results, however, strongly variedacross sessions and conditions.Conclusion: This work shows the transition of a paradigm from healthy subjects to MCS patients. Promisingresults with healthy subjects are, however, no guarantee of good results with patients. Therefore, moreinvestigations are required before any definite conclusions about the usability of this paradigm for MCSpatients can be drawn. Nevertheless, this paradigm might offer an opportunity to support bedside clinicalassessment of MCS patients and eventually, to provide them with a means of communication.
Research Center/Unit :
GIGA CRC (Cyclotron Research Center) In vivo Imaging-Aging & Memory - ULiège
Disciplines :
Engineering, computing & technology: Multidisciplinary, general & others
Author, co-author :
Pokorny, Christoph
Klobassa, Daniela
Pichler, Gerald
Erlbeck, Helena
Real, Ruben
Kübler, Andrea
Lesenfants, Damien ; Université de Liège - ULiège > Centre de recherches du cyclotron
Habbal, Dina ; Université de Liège - ULiège > Form. doc. sc. méd.
Noirhomme, Quentin ; Université de Liège - ULiège > Centre de recherches du cyclotron
Risetti, Monica
Mattia, Donatella
Müller-Putz, Gernot
Language :
English
Title :
The auditory P300-based single-switch brain–computer interface:Paradigm transition from healthy subjects to minimally consciouspatients
Publication date :
October 2013
Journal title :
Artificial Intelligence in Medicine
ISSN :
0933-3657
eISSN :
1873-2860
Publisher :
Elsevier Science, Amsterdam, Netherlands
Volume :
59
Issue :
2
Pages :
81-90
Peer reviewed :
Peer Reviewed verified by ORBi
European Projects :
FP7 - 247919 - DECODER - Deployment of Brain-Computer Interfaces for the Detection of Consciousness in Non-Responsive Patients
Wolpaw J.R., Birbaumer N., McFarland D.J., Pfurtscheller G., Vaughan T.M. Brain-computer interfaces for communication and control. Clinical Neurophysiology 2002, 113:767-791.
Birbaumer N., Ghanayim N., Hinterberger T., Iversen I., Kotchoubey B., Kübler A., et al. A spelling device for the paralysed. Nature 1999, 398:297-298.
Neuper C., Müller G.R., Kübler A., Birbaumer N., Pfurtscheller G. Clinical application of an EEG-based brain-computer interface: a case study in a patient with severe motor impairment. Clinical Neurophysiology 2003, 114:399-409.
Kübler A., Furdea A., Halder S., Hammer E.M., Nijboer F., Kotchoubey B. A brain-computer interface controlled auditory event-related potential (P300) spelling system for locked-in patients. Annals of the New York Acadamy of Sciences 2009, 1157:90-100.
Rebsamen B., Guan C., Zhang H., Wang C., Teo C., Ang M.H., et al. A brain controlled wheelchair to navigate in familiar environments. IEEE Transactions on Neural Systems and Rehabilitation Engineering 2010, 18:590-598.
Galán F., Nuttin M., Lew E., Ferrez P.W., Vanacker G., Philips J., et al. A brain-actuated wheelchair: asynchronous and non-invasive brain-computer interfaces for continuous control of robots. Clinical Neurophysiology 2008, 119:2159-2169.
Müller-Putz G.R., Scherer R., Pfurtscheller G., Rupp R. EEG-based neuroprosthesis control: a step towards clinical practice. Neuroscience Letters 2005, 382:169-174.
Daly I., Billinger M., Laparra-Hernández J., Aloise F., García M.L., Faller J., et al. On the control of brain-computer interfaces by users with cerebral palsy. Clinical Neurophysiology 2013, 124:1787-1797.
Kotchoubey B., Lang S., Mezger G., Schmalohr D., Schneck M., Semmler A., et al. Information processing in severe disorders of consciousness: vegetative state and minimally conscious state. Clinical Neurophysiology 2005, 116:2441-2453.
Monti M., Vanhaudenhuyse A., Coleman M., Boly M., Pickard J., Tshibanda L., et al. Willful modulation of brain activity in disorders of consciousness. The New England Journal of Medicine 2010, 362:579-589.
Giacino J.T., Kalmar K., Whyte J. The JFK coma recovery scale-revised: measurement characteristics and diagnostic utility. Archives of Physical Medicine and Rehabilitation 2004, 85:2020-2029.
Giacino J.T., Schnakers C., Rodriguez-Moreno D., Kalmar K., Schiff N., Hirsch J. Behavioral assessment in patients with disorders of consciousness: gold standard or fool's gold?. Progress in Brain Research 2009, vol. 177:33-48. Elsevier. N.D. Schiff, S. Laureys, A.M. Owen (Eds.).
Pokorny C., Breitwieser C., Neuper C., Müller-Putz G.R. Towards a single-switch BCI based on steady-state somatosensory evoked potentials, in: Proceedings of the 5th International BCI Confonference (Verlag der Technischen Universität Graz) 2011, 200-203.
Müller-Putz G.R., Pokorny C., Klobassa D.S., Horki P. A single switch BCI based on passive and imagined movements: towards restoring communication in minimally conscious patients. International Journal of Neural Systems 2013, 23:1250037.
Zickler C., Riccio A., Leotta F., Hillian-Tress S., Halder S., Holz E., et al. A brain-computer interface as input channel for a standard assistive technology software. Clinical EEG and Neuroscience 2011, 42:236-244.
Chatelle C., Chennu S., Noirhomme Q., Cruse D., Owen A., Laureys S. Brain-computer interfacing in disorders of consciousness. Brain Injury 2012, 26:1510-1522.
Lulé D., Noirhomme Q., Kleih S., Chatelle C., Halder S., Demertzi A., et al. Probing command following in patients with disorders of consciousness using a brain-computer interface. Clinical Neurophysiology 2013, 124:101-106.
Sellers E. New horizons in brain-computer interface research. Clinical Neurophysiology 2013, 124:2-4.
Laureys S., Faymonville M.-E., Degueldre C., Del Fiore G., Damas P., Lambermont B., et al. Auditory processing in the vegetative state. Brain 2000, 123:1589-1601.
Perrin F., Schnakers C., Schabus M., Degueldre C., Goldman S., Brédart S., et al. Brain response to one's own name in vegetative state, minimally conscious state, and locked-in syndrome. Archives of Neurology 2006, 63:562-569.
Di H.B., Yu S.M., Weng X.C., Laureys S., Yu D., Li J.Q., et al. Cerebral response to patient's own name in the vegetative and minimally conscious states. Neurology 2007, 68:895-899.
Murguialday A.R., Hill J., Bensch M., Martens S., Halder S., Nijboer F., et al. Transition from the locked in to the completely locked-in state: a physiological analysis. Clinical Neurophysiology 2011, 122:925-933.
Farwell L.A., Donchin E. Talking off the top of your head: toward a mental prosthesis utilizing event-related brain potentials. Electroencephalography and Clinical Neurophysiology 1988, 70:510-523.
Furdea A., Halder S., Krusienski D.J., Bross D., Nijboer F., Birbaumer N., et al. An auditory oddball (P300) spelling system for brain-computer interfaces. Psychophysiology 2009, 46:1-9.
Halder S., Rea M., Andreoni R., Nijboer F., Hammer E.M., Kleih S.C., et al. An auditory oddball brain-computer interface for binary choices. Clinical Neurophysiology 2010, 121:516-523.
Hill N.J., Lal T.N., Bierig K., Birbaumer N., Schölkopf B. An auditory paradigm for brain-computer interfaces. Advances in Neural Information Processing Systems 2005, 17:569-576.
Hill N.J., Schölkopf B. An online brain-computer interface based on shifting attention to concurrent streams of auditory stimuli. Journal of Neural Engineering 2012, 9:026011.
Kanoh S., Miyamoto K., Yoshinobu T. A brain-computer interface (BCI) system based on auditory stream segregation. Journal of Biomechanical Science and Engineering 2010, 5:32-40.
Müller-Putz G.R., Klobassa D.S., Pokorny C., Pichler G., Erlbeck H., Real R.G.L., et al. The auditory P300-based ssBCI: a door to minimally conscious patients?. Proceedings of the 34th Annual International Conference of the IEEE EMBS 2012, 4672-4675.
Bidet-Caulet A., Bertrand O. Neurophysiological mechanisms involved in auditory perceptual organization. Frontiers in Neuroscience 2009, 3:182-191.
Hillyard S.A., Hink R.F., Schwent V.L., Picton T.W. Electrical signs of selective attention in the human brain. Science 1973, 182:177-180.
Acoustics - Normal equal-loudness-level contours (ISO 226:2003),;1; International Organization for Standardization, Geneva, Switzerland, 2003. URL http://www.iso.org/ (Accessed: 14 July 2013).
Müller-Putz G.R., Scherer R., Brunner C., Leeb R., Pfurtscheller G. Better than random? A closer look on BCI results. International Journal of Bioelectromagnetism 2008, 10:52-55.
Fischer C., Dailler F., Morlet D. Novelty P3 elicited by the subject's own name in comatose patients. Clinical Neurophysiology 2008, 119:2224-2230.
Fischer C., Luaute J., Morlet D. Event-related potentials (MMN and novelty P3) in permanent vegetative or minimally conscious states. Clinical Neurophysiology 2010, 121:1032-1042.
Lavie N. Distracted and confused?. Selective attention under load. Trends in Cognitive Sciences 2005, 9:75-82.
Boly M., Faymonville M., Peigneux P., Lambermont B., Damas P., Del Fiore G., et al. Auditory processing in severely brain injured patients: Differences between the minimally conscious state and the persistent vegetative state. Archives of Neurology 2004, 61:233-238.
Kübler A., Neumann N., Wilhelm B., Hinterberger T., Birbaumer N. Predictability of brain-computer communication. Journal of Psychophysiology 2004, 18:121-129.
Maris E., Oostenveld R. Nonparametric statistical testing of EEG- and MEG-data. Journal of Neuroscience Methods 2007, 164:177-190.
Schnakers C., Perrin F., Schabus M., Majerus S., Ledoux D., Damas P., et al. Voluntary brain processing in disorders of consciousness. Neurology 2008, 71:1614-1620.
Kaufmann T., Schulz S., Grünzinger C., Kübler A. Flashing characters with famous faces improves ERP-based brain computer interface performance. Journal of Neural Engeneering 2011, 5:056016.
Manyakov N.V., Chumerin N., Combaz A., Van Hulle M.M. Comparison of classification methods for P300 brain-computer interface on disabled subjects. Computational Intelligence and Neuroscience 2011, 519868.
Krusienski D.J., Sellers E.W., Cabestaing F., Bayoudh S., McFarland D.J., Vaughan T.M., et al. A comparison of classification techniques for the P300 speller. Journal of Neural Engineering 2006, 3:299-305.
