Brain-Computer Interfaces for Assessment and Communication in Disorders of Consciousness

Brain-Computer Interfaces for Assessment and Communication in Disorders of Consciousness

Christoph Guger (Guger Technologies, Austria), Bettina Sorger (Maastricht University, The Netherlands), Quentin Noirhomme (University of Liege, Belgium), Lorina Naci (University of Western Ontario, Canada), Martin M. Monti (University of California, Los Angeles, USA), Ruben Real (Universität Würzburg, Germany), Christoph Pokorny (Graz University of Technology, Austria), Sandra Veser (University of Tübingen, Germany), Zulay Lugo (University of Liège, Belgium), Lucia Quitadamo (“Tor Vergata” University of Rome, Italy), Damien Lesenfants (Université de Liège, Belgium), Monica Risetti (Fondazione Santa Lucia, IRCCS, Italy), Rita Formisano (Fondazione Santa Lucia, IRCCS, Italy), Jlenia Toppi (“Sapienza” University of Rome, Italy), Laura Astolfi (“Sapienza” University of Rome, Italy), Thomas Emmerling (Maastricht University, The Netherlands), Lizette Heine (Maastricht University, The Netherlands), Helena Erlbeck (Universität Würzburg, Germany), Petar Horki (Graz University of Technology, Austria), Boris Kotchoubey (University of Tübingen, Germany), Luigi Bianchi (“Tor Vergata” University of Rome, Italy), Donatella Mattia (Fondazione Santa Lucia, IRCCS, Italy), Rainer Goebel (Maastricht University, The Netherlands), Adrian M. Owen (Western University, Canada), Frederic Pellas (Association Locked-In Syndrome, France), Gernot Müller-Putz (Graz University of Technology, Austria), Steven Laureys (University of Liege, Belgium), Andrea Kübler (Universität Würzburg, Germany) and Febo Cincotti (“Sapienza” University of Rome, Italy)
Copyright: © 2014 |Pages: 34
DOI: 10.4018/978-1-4666-6094-6.ch010

Abstract

Many patients with Disorders of Consciousness (DOC) are misdiagnosed for a variety of reasons. These patients typically cannot communicate. Because such patients are not provided with the needed tools, one of their basic human needs remains unsatisfied, leaving them truly locked in to their bodies. This chapter first reviews current methods and problems of diagnoses and assistive technology for communication, supporting the view that advances in both respects are needed for patients with DOC. The authors also discuss possible solutions to these problems and introduce emerging developments based on EEG (Electroencephalography), fMRI (Functional Magnetic Resonance Imaging), and fNIRS (Functional Near-Infrared Spectroscopy) that have been validated with patients and healthy volunteers.
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Introduction

The clinical care and rehabilitation approaches involving patients diagnosed with disorders of consciousness (DOC) are of great medical and social importance. The progressive increase in the number of surviving patients and their increasing life expectancies, in all industrialized countries, reflects the advancement of knowledge and techniques in the field of reanimation, as well as improved quality of care. An accurate early diagnosis is indispensable to develop early and effective standards of care, appropriate to an individual patient’s condition. The clinical diagnosis of these patients is a major challenge because of the very fine line between the Vegetative State/Unresponsive Wakefulness Syndrome (VS/UWS; Laureys et al., 2010), characterized by preserved arousal in the absence of behavioral signs of awareness, the Minimally Conscious State (MCS), with non-reflexive albeit inconstant purposeful behaviors, and the Locked-In Syndrome (LIS), in which consciousness is fully preserved (Giacino et al., 2002). Recent work identified two groups within this patient population - those who show higher-order signs of consciousness (e.g., command following, intelligible verbalization, and non functional communication; i.e. MCS plus) versus those who show only low-level signs of consciousness (e.g., visual pursuit of a salient stimulus, noxious stimulation localization, appropriate emotional response; i.e. MCS minus) (Bruno et al., 2011; Bodart et al., 2013).

Despite the efforts already made to improve the instrumental diagnosis, differential diagnosis between different patients with an altered state of consciousness is eminently clinical and based on a list of items that the patient is unable to perform. The LIS is a term introduced by Plum and Posner to describe a neurological condition of quadriplegia and anarthria associated with ventral pons infarction (Plum & Posner, 1966). The American Congress of Rehabilitation Medicine defined the LIS as: i) the presence of sustained eye opening, ii) the preservation of cognitive skills, iii) a severe hoarseness or hypophonia iv) quadriplegia or quadriparesis, and v) a primary mode of communication using eye movements or blinking (American Congress of Rehabilitation Medicine, 1995). The main etiology of LIS is stroke (Patterson & Grabois, 1986). The diagnosis of this condition is particularly challenging because patients cannot communicate by the usual means. These patients are fully conscious but completely or almost completely unable to move and speak, so they can easily be mistaken for VS patients.

Evidence-based medicine (EBM) has been defined as the integration of current best evidence with clinical experience and patients’ values and preferences in clinical decision-making process (Brownson et al., 2012). With the introduction of EBM, the clinicians are exhorted to consider all three factors in the process to foster the evidence-based-decision-making (EBDM) in public health. These concepts appear of utmost relevance when dealing with disorders of consciousness characterizations, which entail a broad spectrum of entities that are often misdiagnosed.

In this context, the development of brain-computer interface (BCI) tools, as well as other paraclinical instruments and methods, can facilitate the differentiation of these clinical states. BCIs are devices that allow users to communicate directly by means of brain activity. Recently, BCIs have become much more practical and flexible, due to advances such as dry electrodes, high-impedance amplifiers, better interfaces (Kaufmann et al., 2013a), and improved testing with patients in clinical settings (Zickler et al., 2011). Hence, BCIs are becoming useful to broader groups (Guger et al., 2012; Wolpaw and Wolpaw, 2012; Allison et al., 2013).

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