Brain computer Interfaces
Towards next generation human-computer interaction -- brain-computer interfaces: applications and challenges
... the computer via various channels, such as keyboards and ...control. Brain-computer interfaces are systems that measure specific brain activities ...a computer without muscle ...
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OpenViBE: An Open-Source Software Platform to Design, Test and Use Brain-Computer Interfaces in Real and Virtual Environments
... use Brain-Computer Interfaces. Brain-Computer Interfaces (BCI) are communication systems that enable users to send commands to computers only by means of brain ...
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Electroencephalography (EEG)-based Brain-Computer Interfaces
... the brain, and although ERPs are stereotyped deflections, they are difficult to distinguish in a single ...For Brain Computer Interfaces where the analysis must be done in real time, there are ...
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Adaptive machine learning methods for event related potential-based brain computer interfaces
... Les interfaces cerveau machine (BCI pour Brain Computer Interfaces) non invasives permettent à leur utilisateur de contrôler une machine par la ...aux interfaces cerveau machine qui ...
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Verbal Communication through Brain Computer Interfaces
... Brain Computer Interfaces (BCI) provide a way of communi- cating directly from brain activity, bypassing muscular ...virtual brain-operated ...
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Hybrid Brain-Computer Interfaces: Improving Mental Task Classification Performance through Fusion of Neurophysiological Modalities.
... 2. Brain-Computer Interfaces: Recent Advances and Open Challenges 27 reported a passive system to identify images of interest presented to the subjects by analysing EEG and pupil dilation ...and ...
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Uncued brain-computer interfaces: a variational hidden markov model of mental state dynamics
... Uncued brain-computer interfaces: a variational hidden markov model of mental state dynamics.. Cedric Gouy-Pailler, Jérémie Mattout, Marco Congedo, Christian Jutten.[r] ...
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Introduction: Evolution of Brain-Computer Interfaces
... ) Brain-Computer Interfaces (BCIs) are systems that translate a measure of a user‘s brain activity into messages or commands for an interactive ...a computer screen towards the left or ...
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Towards a user-centred methodological framework for the design and evaluation of applications combining brain-computer interfaces and virtual environments: contributions of ergonomics
... combining brain-computer interfaces and virtual environments: contributions of ergonomics Résumé : Ce rapport présente un cadre méthodologique centré sur l’utilisateur visant à assister la conception ...
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Subject-Specific Channel Selection Using Time Information for Motor Imagery Brain–Computer Interfaces
... The probabilities of channels being selected are shown in Fig. 6 . The red areas indicate the important brain areas where the channels are often selected. We also marked out the key channels with the selection ...
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A Review of Classification Algorithms for EEG-based Brain-Computer Interfaces: A 10-year Update
... Adaptive classifiers can employ both supervised and unsupervised adaptation, i.e. with or without knowledge of the true class labels of the incoming data, respectively. With supervised a[r] ...
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Towards Adaptive Classification using Riemannian Geometry approaches in Brain-Computer Interfaces
... To do so, a variety of machine learning methods have been proposed, among which the most efficient ones include Riemannian Geometry-based Classifiers (RGC) and adaptive classifiers [2]. RGC represent EEG signals as ...
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Contribution to the study of the use of brain-computer interfaces in virtual and augmented reality
... Another system proposing to manipulate a robot was designed by Petit et al. in a similar setup where the robot would see the user and interact with her with the help of AR markers [ Petit et al. , 2014 ]. Users were ...
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Trends in BCI Research I: Brain-Computer Interfaces for Assessment of Patients with Locked-in Syndrome or Disorders of Consciousness
... 4 DOC Neurophysiological Assessment at FSL The stability of Event-Related Potentials (ERPs) is essential for ef ficient and effective ERP-based BCI systems, especially when BCIs is applied in a challenging clinical ...
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EEG signal analysis for brain-computer interfaces for large public applications
... BCI competition II dataset IV [ 32 ]: It contains data from a single subject with two finger movements (fingers from left and right hands), recorded using 28 EEG chan- nels, which have been used in [ 110 ] as ...
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Optimizing the use of SSVEP-based brain-computer interfaces for human-computer interaction
... 4.1.3 Experimental design Participants were sitting in front of a computer screen, wearing an EEG headset (see Figure 4.1). Three flickering square targets were displayed on screen. For each trial, the task ...
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Topographical Dynamics of Brain Connections for the Design of Asynchronous Brain-Computer Interfaces
... One can observe that graph analysis gives noisier results. The main cause is the use of correlation measures, which thus have to be replaced by a more stable one. The method using graph analysis shows similar results in ...
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Towards Adaptive Classification using Riemannian Geometry approaches in Brain-Computer Interfaces
... To do so, a variety of machine learning methods have been proposed, among which the most efficient ones include Riemannian Geometry-based Classifiers (RGC) and adaptive classifiers [2]. RGC represent EEG signals as ...
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A robust sensor-selection method for P300 brain-computer interfaces.
... interface that enables the direct communication between human and computers through decoding of brain activity. As such, event-related potentials (ERPs) like the P300 can be obtained with an oddball paradigm whose ...
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Extending Riemannian Brain-Computer Interface to Functional Connectivity Estimators
... Riemannian Brain-Computer Interface to Functional Connectivity Estimators Sylvain Chevallier 1 , Marie-Constance Corsi 2 , Florian Yger 3 and Camille Noˆus 4 Abstract— This abstract describes a novel ...
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