Hybrid BCI Coupling EEG and EMG for Severe Motor Disabilities

AbstractIn this paper, we are studying hybrid Brain-Computer Interfaces (BCI) coupling joystick data, electroencephalogram (EEG – electrical activity of the brain) and electromyogram (EMG – electrical activity of muscles) activities for severe motor disabilities. We are focusing our study on muscular activity as a control modality to interact with an application. We present our data processing and classification technique to detect right and left hand movements. EMG modality is well adapted for DMD patients, because less strength is needed to detect movements in contrast to conventional interfaces like joysticks. Across virtual reality tools, we believe that users will be more able to understand how to interact with such kind of interactive systems. This first part of our study report some very good results concerning the detection of hand movements, according to muscular channel, on healthy subjects

Modélisation et reconnaissance de signes par décomposition en "gestèmes" géométriques (application à la langue des signes françaises)

Notre étude traite de la reconnaissance de signes de la langue des signes. Pour identifier une séquence gestuelle inconnue, nous défmissons des entités de base auxquelles nous associons des modèles mathématiques. Ensuite, nous recherchons dans un signal gestuel inconnu la présence de ces entités, qui constituent l'énoncé en se combinant suivant une grammaire. Nous étudions la faisabilité d'une reconnaissance de signes à partir d'entités en nombre limité et plus petites que le signe. En particulier, nous privilégions le mouvement de la main pour faire un découpage du signe. Les entités retenues sont des segments de trajectoires sous forme d'arcs de cercles et de droites. Nous avons utilisé le couple caméra-ordinateur pour proposer un système de vision et de prise de décision qui saisit le geste de l'utilisateur et identifie le contenu du message transmis. L'approche de modélisation proposée a été testée dans un cadre probabiliste markovien sur un corpus de signes.LILLE1-BU (590092102) / SudocSudocFranceF

Evidential Matrix Metrics as Distances Between Meta-Data Dependent Bodies of Evidence

International audienceAs part of the theory of belief functions, we address the problem of ap-praising the similarity between bodies of evidence in a relevant way using metrics. Such metrics are called evidential distances and must be com-puted from mathematical objects depicting the information inside bodies of evidence. Specialization matrices are such objects and, therefore, an evidential distance can be obtained by computing the norm of the differ-ence of these matrices. Any matrix norm can be thus used to define a full metric. In this article, we show that other matrices can be used to obtain new evidential distances. These are the α-specialization and α-generalization matrices and are closely related to the α-junctive combination rules. We prove that any L 1 norm-based distance thus defined is consistent with its corresponding α-junction. If α > 0, these distances have in addition relevant variations induced by the poset structure of the belief function domain. Furthermore, α-junctions are meta-data dependent combination rules. The meta-data involved in α-junctions deals with the truthfulness of information sources. Consequently, the behavior of such evidential distances is analyzed in situations involving uncertain or partial meta-knowledge about information source truthfulness

Toward a SSSEP-Based BCI Using the Sensory Gating Phenomenon

International audienceA physiological phenomenon named movement-related sensory gating has been described in the literature in the late 80s. To the best of our knowledge, it has not yet been exploited in the BCI domain. We consider that this phenomenon could significantly decrease the resonance-like frequency of Steady State Somatosensory Evoked Potentials (SSSEP) and be exploited as a voluntary command of the user will. We describe our work to retrieve a resonance in user's EEG while applying vibrations under their fingers. Our first results confirm previous works reported in literature concerning SSSEP. We report SSSEP detected on four healthy subjects who received tactile vibration under their right and left index finger at five different frequencies (14, 17, 20, 23 and 26 Hz). The mechanical stimulation was created by a device conceived in our laboratory. This device is based on two C2-tactors piloted by an Arduino. We think that a SSSEP-based BCI using the sensory gating phenomenon could be used soon by DMD (Duchenne Muscular Dystrophy) patients that can perceive vibrations under their skin but are no more able to perform voluntary movements

Supervising SSSEP experiments with a Bluetooth Android remote control application

International audienceIn this paper, we are presenting how we are controlling the vibration frequency sent from an Android smartphone to an Arduino board connected to a vibrator, in order to supervise more easily SSSEP (Steady State Somatosensory Evoked Potentials) experiments. Our researches are conducted in the context of hybrid Brain-Computer Interfaces for motor severely impaired patients, and our aim is to detect a physiological gating phenomenon on SSSEP responses when patients are trying to perform some small fingers moves while vibrations are emitted under their fingers

Classification crédale multi-cibles - Multi-target evidential classification

International audienceIn this paper, we study the problem of joint tracking and classification of several targets. Targets are considered to be known and sufficiently separated so that they cannot be confused. Our goal is to shed light on the contribution of credal classification over the Bayesian classification. Our job is to track the movement of targets using conventional Kalman filters and IMMs, and compare the performances of credal and Bayesian classification

Classification crédale multi-cibles - Multi-target evidential classification

International audienceIn this paper, we study the problem of joint tracking and classification of several targets. Targets are considered to be known and sufficiently separated so that they cannot be confused. Our goal is to shed light on the contribution of credal classification over the Bayesian classification. Our job is to track the movement of targets using conventional Kalman filters and IMMs, and compare the performances of credal and Bayesian classification

Expérimentation des interfaces cerveau-ordinateur: une approche globale basée sur les facteurs humains

International audienceThe development of new enabling devices is one of the most credible short and medium-term applications of brain-computer interfaces (BCI). Unlike many other recent assistive technologies (AT), present BCI systems usually do not result from a "design for all" approach, since they are mainly effective for people suffering from severe motor disabilities. However, many authors have shown that it is crucial to take into account adaptability, flexibility, customisability and other ergonomics related criteria while designing a BCI-based AT. In this paper, we specify a framework that could expedite the transferability of BCI experiments from labs to clinical departments and later to patients' homes. We highlight the interest of designing dedicated experimentation facilities (namely a Room for BCI Experimentation or RBCIE) in which the developed BCI systems can be efficiently tested and validated. More generally, we highlight the interest of a multidisciplinary design approach introducing human factors at the core of concerns.Le développement de nouveaux systèmes d'aide à la personne est l'une des applications des interfaces cerveau ordinateur (BCI) les plus probables à court et moyen terme. Contrairement à de nombreuses technologies d'assistance récentes, les systèmes BCI actuels ne résultent pas d'une approche de conception universelle. De nombreux auteurs ont montré l'importance de prendre en compte des critères comme l'adaptabilité, la flexibilité, et autres critères relatifs à l'ergonomie lors de la conception d'une interface BCI. Dans cet article, nous proposons un cadre de travail visant à accélérer le transfert des expérimentations BCIs des laboratoires de recherche vers les services cliniques puis aux domiciles des patients. Plus précisément, nous montrons l'intérêt de concevoir une salle d'expérimentation dédiée, appelée « Room for BCI Experimentation » ou RBCIE, où les interfaces BCI peuvent être testées et validées efficacement

Relevant HCI for Hybrid BCI and Severely Impaired Patients

International audienceIn this paper, we are studying the possibility to enhance the relevance of hybrid Brain-Computer Interfaces for severely impaired patients by improving the relevance of Human-Computer Interfaces. Across virtual reality tools and serious games approaches, we believe that users will be more able to understand how to interact with such kind of interactive systems