AUTHOR=Galiotta Valentina , Quattrociocchi Ilaria , D'Ippolito Mariagrazia , Schettini Francesca , Aricò Pietro , Sdoia Stefano , Formisano Rita , Cincotti Febo , Mattia Donatella , Riccio Angela 

TITLE=EEG-based Brain-Computer Interfaces for people with Disorders of Consciousness: Features and applications. A systematic review

JOURNAL=Frontiers in Human Neuroscience

VOLUME=Volume 16 - 2022

YEAR=2022

URL=https://www.frontiersin.org/journals/human-neuroscience/articles/10.3389/fnhum.2022.1040816

DOI=10.3389/fnhum.2022.1040816

ISSN=1662-5161

ABSTRACT=Disorders of Consciousness (DoC) are clinical conditions following a severe acquired brain injury (ABI) characterized by absent or reduced awareness, known as coma, Vegetative State (VS)/Unresponsive Wakefulness Syndrome (VS/UWS), and Minimally Conscious State (MCS). Misdiagnosis rate between VS/UWS and MCS is attested around 40% due to the clinical and behavioral fluctuations of the patients during bedside consciousness assessments. Given the large body of evidence that some patients with DoC possess “covert” awareness, revealed by neuroimaging and neurophysiological techniques, they are candidates for intervention with brain-computer interfaces (BCIs). The aim of the present work is to describe the characteristics of BCI systems based on electroencephalography (EEG) evaluated in DoC patients, in terms of control signals adopted to control the system, characteristics of the paradigm implemented, classification algorithms and applications and to evaluate the performance of DoC patients with BCI. Among the 527 papers identified with the first run of the search, 27 papers were included in the systematic review. Data extracted from the studies were related to the characteristics of the sample of participants and behavioral assessment, the control signals employed to control the BCI and the classification algorithms, the characteristics of the paradigm, the applications and performance of BCI. The control signals used to control the BCI were: P300 (N=19), P300 and Steady-State Visual Evoked Potentials (SSVEP; hybrid system, N=4), sensorimotor rhythms (SMRs; N=5) and brain rhythms elicited by an emotional task (N=1). The possible applications of BCI with DoC patients were: assessment, communication, prognosis, and rehabilitation. The P300 is the most widespread control signal used to control a BCI and the assessment is the most frequent application. Despite the BCI is a promising tool in the management of DoC patients, supporting diagnosis and prognosis evaluation, results are still preliminary, and no definitive conclusions may be drawn; even though neurophysiological methods, such as BCI, are more sensitive to covert cognition, it is mandatory to adopt a multimodal approach and a repeated assessment strategy.