A vibrotactile P300-based BCI for consciousness detection and communication

Brain–computer interface (BCI) has been used for many years for communication in severely disabled patients. BCI based on electrophysiological signals has enabled communication, using auditory or visual stimuli to elicit event-related potentials (ERPs). The aim of this study was to determine whether patients with locked-in syndrome (LIS) could elicit a P300 wave, using a vibrotactile oddball paradigm for establishing somatosensory BCI-based communication. Six chronic LIS patients performed 2electroencephalography (EEG)-based vibrotactile P300 oddball tasks. After a simple mental counting task of the target stimuli, participants were instructed to answer 5 questions by counting the vibration on either the right wrist for “yes” or the left wrist for “no.” All participants were able to elicit a P300 wave using the vibrotactile oddball paradigm BCI task. In the counting task, 4 patients got accuracies of 100% (average above chance). In the communication task, one patient achieved 100% accuracy (average above chance). We have shown the feasibility of eliciting a P300 response using vibrotactile stimulation in patients with LIS. The present study provides evidence that this approach can be used for EEG-based BCI communications in this patient group. This is the first study to prove the feasibility of a BCI based on somatosensory (vibratory) stimulation in a group of braininjured patients. Furthermore, this approach could be used for the detection of consciousness in non-communicating patients due to severe brain injuries.

[1]  Touradj Ebrahimi,et al.  An efficient P300-based brain–computer interface for disabled subjects , 2008, Journal of Neuroscience Methods.

[2]  M Rousseaux,et al.  Evidence of persisting cognitive impairment in a case series of patients with locked-in syndrome , 2008, Journal of Neurology, Neurosurgery, and Psychiatry.

[3]  M. Boly,et al.  Diagnostic accuracy of the vegetative and minimally conscious state: Clinical consensus versus standardized neurobehavioral assessment , 2009, BMC neurology.

[4]  Marina Schmid,et al.  An Introduction To The Event Related Potential Technique , 2016 .

[5]  Steven Laureys,et al.  Brain–computer interfacing in disorders of consciousness , 2012, Brain injury.

[6]  Niels Birbaumer,et al.  Is there a mind? Electrophysiology of unconscious patients. , 2002, News in physiological sciences : an international journal of physiology produced jointly by the International Union of Physiological Sciences and the American Physiological Society.

[7]  E. John,et al.  Evoked-Potential Correlates of Stimulus Uncertainty , 1965, Science.

[8]  N. Birbaumer,et al.  Information processing in severe disorders of consciousness: Vegetative state and minimally conscious state , 2005, Clinical Neurophysiology.

[9]  E. Sellers,et al.  How many people are able to control a P300-based brain–computer interface (BCI)? , 2009, Neuroscience Letters.

[10]  J. Polich Clinical application of the P300 event-related brain potential. , 2004, Physical medicine and rehabilitation clinics of North America.

[11]  A. Kübler,et al.  A Brain–Computer Interface Controlled Auditory Event‐Related Potential (P300) Spelling System for Locked‐In Patients , 2009, Annals of the New York Academy of Sciences.

[12]  G. Riva,et al.  The use of P300-based BCIs in amyotrophic lateral sclerosis: from augmentative and alternative communication to cognitive assessment , 2012, Brain and behavior.

[13]  Brendan Z. Allison,et al.  P300 brain computer interface: current challenges and emerging trends , 2012, Front. Neuroeng..

[14]  J. Polich Updating P300: An integrative theory of P3a and P3b , 2007, Clinical Neurophysiology.

[15]  Steven Laureys,et al.  Probing command following in patients with disorders of consciousness using a brain–computer interface , 2013, Clinical Neurophysiology.

[16]  Jan B. F. van Erp,et al.  A Tactile P300 Brain-Computer Interface , 2010, Front. Neurosci..

[17]  Steve Majerus,et al.  Cognitive function in the locked-in syndrome , 2008, Journal of Neurology.

[18]  J. Giacino,et al.  The minimally conscious state: Definition and diagnostic criteria , 2002, Neurology.

[19]  Jonathan R Wolpaw,et al.  A brain-computer interface for long-term independent home use , 2010, Amyotrophic lateral sclerosis : official publication of the World Federation of Neurology Research Group on Motor Neuron Diseases.

[20]  Steve Majerus,et al.  Detecting Consciousness in a Total Locked-in Syndrome: an Active Event-related Paradigm Detecting Consciousness in a Total Lis , 2022 .

[21]  L. Cohen,et al.  Brain–computer interfaces: communication and restoration of movement in paralysis , 2007, The Journal of physiology.

[22]  G. Pfurtscheller,et al.  Brain-Computer Interfaces for Communication and Control. , 2011, Communications of the ACM.

[23]  Steven Laureys,et al.  Locked-in syndrome in children: report of five cases and review of the literature. , 2009, Pediatric neurology.

[24]  Walter G Sannita,et al.  Unresponsive wakefulness syndrome: a new name for the vegetative state or apallic syndrome , 2010, BMC medicine.

[25]  F. Plum,et al.  The diagnosis of stupor and coma. , 1972, Contemporary neurology series.

[26]  J. Leon-Carrion,et al.  Review of subject: The locked-in syndrome: a syndrome looking for a therapy , 2002, Brain injury.

[27]  R. Goebel,et al.  Brain–computer interfaces for communication with nonresponsive patients , 2012, Annals of neurology.