Assessing Command-Following and Communication With Vibro-Tactile P300 Brain-Computer Interface Tools in Patients With Unresponsive Wakefulness Syndrome

Abstract

Persons diagnosed with disorders of consciousness (DOC) typically suffer from motor disablities, and thus assessing their spared cognitive abilities can be difficult. Recent research from several groups has shown that non-invasive brain-computer interface (BCI) technology can provide assessments of these patients' cognitive function that can supplement information provided through conventional behavioral assessment methods. In rare cases, BCIs may provide a binary communication mechanism. Here, we present results from a vibrotactile BCI assessment aiming at detecting command-following and communication in 12 unresponsive wakefulness syndrome (UWS) patients. Two different paradigms were administered at least once for every patient: (i) VT2 with two vibro-tactile stimulators fixed on the patient's left and right wrists and (ii) VT3 with three vibro-tactile stimulators fixed on both wrists and on the back. The patients were instructed to mentally count either the stimuli on the left or right wrist, which may elicit a robust P300 for the target wrist only. The EEG data from −100 to +600 ms around each stimulus were extracted and sub-divided into 8 data segments. This data was classified with linear discriminant analysis (using a 10 × 10 cross validation) and used to calibrate a BCI to assess command following and YES/NO communication abilities. The grand average VT2 accuracy across all patients was 38.3%, and the VT3 accuracy was 26.3%. Two patients achieved VT3 accuracy ≥80% and went through communication testing. One of these patients answered 4 out of 5 questions correctly in session 1, whereas the other patient answered 6/10 and 7/10 questions correctly in sessions 2 and 4. In 6 other patients, the VT2 or VT3 accuracy was above the significance threshold of 23% for at least one run, while in 4 patients, the accuracy was always below this threshold. The study highlights the importance of repeating EEG assessments to increase the chance of detecting command-following in patients with severe brain injury. Furthermore, the study shows that BCI technology can test command following in chronic UWS patients and can allow some of these patients to answer YES/NO questions.

Wheelchair Control in a Virtual Environment by Healthy Participants Using a P300-BCI Based on Tactile Stimulation: Training Effects and Usability

“…Examples include a tactile spelling BCI by van der Waal et al ( 2012 ) which used small taps on the fingertips, administered by a braille stimulator, to achieve a mean accuracy of 67% among a sample of twelve healthy participants, and one of the earliest publications, where up to six vibrotactile devices were located around the waist of healthy participants, achieving a 58% mean accuracy (73% for two devices; Brouwer and van Erp, 2010 ). Notably, several studies demonstrated that the tactile modality can be feasible for BCI control by severely impaired potential end-users (Lugo et al, 2014 ; Ortner et al, 2014 ; Severens et al, 2014 ; Guger et al, 2018 ).…”

Auditory and Somatosensory P3 Are Complementary for the Assessment of Patients with Disorders of Consciousness

“…To evaluate if the true positive rate was above chance level, which we refer here as ‘differentiated response’, two different approaches were used. In the ‘direct processing’, the significance level was set at 23% (binomial test, n = 60 trials, alpha = 0.05, for more details, see the previous studies in completely locked-in syndrome [ 30 ] and UWS [ 31 ] patients). In the ‘offline processing’, a subject-specific level of significance was computed using a permutation test (as described in [ 32 , 33 ], 1000 repetitions, p < 0.05).…”

Beyond Technologies of Electroencephalography-Based Brain-Computer Interfaces: A Systematic Review From Commercial and Ethical Aspects

“…Moreover, EEG is also used as an initial diagnosis assessment tool alternative to MRI and CT-SCAN due to its costeffectiveness. Here, EEG systems have proven valuable in the diagnosis of disorders of consciousness (DOC) (Guger et al, 2018;Stefan et al, 2018) as well as in the detection of tumors and concussions (Selvam and Shenbagadevi, 2011;Sharanreddy and Kulkarni, 2013;Abdulkader et al, 2015). For DOC diagnosis purposes, the Austrian company Guger Technologies (g.tec) has developed the EEG-based system mindBEAGLE (Figure 4), which provides quick and easy assessments of DOC and basic communication with certain patients (Spataro et al, 2018).…”