The auditory p300-based SSBCI: A door to minimally conscious patients?

Müller-Putz, Gernot; Klobassa, Daniela S.; Pokorny, Christoph; Pichler, Gerhard; Erlbeck, Helena; Real, Ruben; Kübler, Andrea; Risetti, Monica; Mattia, Donatella

doi:10.1109/embc.2012.6347009

Cited by 13 publications

(14 citation statements)

References 18 publications

(18 reference statements)

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“…Our main question was, whether a paradigm that is promising in healthy subjects can also successfully be applied to MCS patients. Some preliminary results of this work have already been presented in [30].…”

Section: Introductionmentioning

confidence: 92%

The auditory P300-based single-switch brain–computer interface: Paradigm transition from healthy subjects to minimally conscious patients

Pokorny

Klobassa

Pichler

et al. 2013

Artificial Intelligence in Medicine

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Objective: Within this work an auditory P300 brain-computer interface (BCI) based on tone stream segregation, which allows for binary decisions, was developed and evaluated. Materials and methods: Two tone streams consisting of short beep tones with infrequently appearing deviant tones at random positions were used as stimuli. This paradigm was evaluated in 10 healthy subjects and applied to 12 patients in a minimally conscious state (MCS) at clinics in Graz, Würzburg, Rome, and Liège. A stepwise linear discriminant analysis (SWLDA) classifier with 10 × 10 cross-validation was used to 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 than random. However, for MCS patients only a small number of classification results were above chance level and none of the results were sufficient for communication purposes. Nevertheless, signs of consciousness were detected in most patients, not on a single-trial basis, but after averaging of corresponding data segments and computing significant differences. These significant results, however, strongly varied across sessions and conditions. Conclusion: This work shows the transition of a paradigm from healthy subjects to MCS patients. Promising results with healthy subjects are, however, no guarantee of good results with patients. Therefore, more investigations are required before any definite conclusions about the usability of this paradigm for MCS patients can be drawn. Nevertheless, this paradigm might offer an opportunity to support bedside clinical assessment of MCS patients and eventually, to provide them with a means of communication.

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Section: Introductionmentioning

confidence: 92%

The auditory P300-based single-switch brain–computer interface: Paradigm transition from healthy subjects to minimally conscious patients

Pokorny

Klobassa

Pichler

et al. 2013

Artificial Intelligence in Medicine

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“…As regard P3, it could be obtained in 20-25 % of DoC patients (Witzke and Schönle 1996 ; Kotchoubey et al 2001Kotchoubey et al , 2005Cavinato et al 2009 [only traumatic VS/UWS patients], Schnakers et al 2008 [P3 found only in MCS but not in VS/UWS], Müller-Putz et al 2012 ;Guger et al 2013 ;Steppacher et al 2013 ). This may indicate activation of complex cortico-subcortical networks in response to target stimuli in many patients.…”

Section: Erp Manifest Remaining Cognitive Processes In Doc Patientsmentioning

confidence: 98%

Clinical Neurophysiology in Disorders of Consciousness

Rossetti¹,

Laureys²

2015

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“…As argued in (Lotte et al 2018), no signal analysis techniques would be able to recognize (decode) specific command patterns if the user is unable to produce (encode) them. For example, the subject could be: unable to receive an input from the system (stimulus, feedback or information about the state of the BCI); potentially alarmed or scared by the stimulus (Schreuder, Blankertz, and Tangermann 2010;Müller-Putz et al 2012); unable to focus on the required mental task; unable to continuously focus on the assigned task. The inconstancy of the user mood, stress, engagement, and level of attention is also a cause of the BCI performance variability and should be taken in account (Friedrich et al 2015;Pammer-Schindler et al 2017).…”

Section: Bci Illiteracymentioning

confidence: 99%

Towards EEG-based BCI driven by emotions for addressing BCI-Illiteracy: a meta-analytic review

Spezialetti

Cinque

Tavares

et al. 2018

Behaviour & Information Technology

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Many critical aspects affect the correct operation of a Brain Computer Interface. The term "BCIilliteracy" describes the impossibility of using a BCI paradigm. At present, a universal solution does not exist and seeking innovative protocols to drive a BCI is mandatory. This work presents a meta-analytic review on recent advances in emotions recognition with the perspective of using emotions as voluntary, stimulus-independent, commands for BCIs. 60 papers, based on electroencephalography measurements, were selected to evaluate what emotions have been most recognized and what brain regions were activated by them. It was found that happiness, sadness, anger and calm were the most recognized emotions. Most discriminant locations for emotions recognition and for the particular case of discrete emotions recognition were identified in the temporal, frontal and parietal areas. The meta-analysis was mainly performed on stimulus-elicited emotions, due to the limited amount of literature about self-induced emotions. The obtained results represent a good starting point for the development of BCI driven by emotions and allow to: 1) ascertain that emotions are measurable and recognizable one from another 2) select a subset of most recognizable emotions and the corresponding active brain regions.

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The auditory p300-based SSBCI: A door to minimally conscious patients?

Cited by 13 publications

References 18 publications

The auditory P300-based single-switch brain–computer interface: Paradigm transition from healthy subjects to minimally conscious patients

The auditory P300-based single-switch brain–computer interface: Paradigm transition from healthy subjects to minimally conscious patients

Clinical Neurophysiology in Disorders of Consciousness

Towards EEG-based BCI driven by emotions for addressing BCI-Illiteracy: a meta-analytic review

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