Brain-Machine Interfaces
Direct growth of carbon nanotubes on new high-density 3D pyramid-shaped microelectrode arrays for brain-machine interfaces
... Keywords: brain-machine interface; microelectrode arrays; microfabrication technologies; carbon nanotubes; electrode Impedance ...called brain-machine interfaces (BMI), enable direct ...
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Cognitive signals for brain–machine interfaces in posterior parietal cortex include continuous 3D trajectory commands
... the brain with the goal to restore function in paralyzed or amputated ...’ brain-control performance improved rapidly with practice, resulting in faster target acquisition and increasing ...
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Cognitive signals for brain–machine interfaces in posterior parietal cortex include continuous 3D trajectory commands
... the brain-control de- code session and (ii) monitoring the EMG activity of the muscle groups typically involved in reaching movements in monkey ...the brain control session during a series of reach ...
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Spiking Neural Network Decoder for Brain-Machine Interfaces
... of brain-machine interface performance in both human [5] and monkey users [2], these simulations provide confidence that similar levels of performance can be attained with a neuromorphic ...
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Design and validation of a real-time spiking-neural-network decoder for brain–machine interfaces
... processing. Such a filter and its variants have demonstrated the highest levels of brain- machine interface (BMI) performance in both humans [5] and monkeys [4]. Even though successes with non-linear ...
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Topographical Dynamics of Brain Connections for the Design of Asynchronous Brain-Computer Interfaces
... of brain-machine interfaces (BMIs) is to provide disabled people suffering from severe motor diseases with a tool to restore communication and movement ...However brain- machine ...
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A Brain-Machine Interface Operating with a Real-Time Spiking Neural Network Control Algorithm
... the brain into useful control signals for prosthetic limbs or computer ...for brain-machine interfaces (BMIs) in humans [5] and monkeys ...the brain by more than 1 ◦ C [6], which is ...
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Towards Adaptive Classification using Riemannian Geometry approaches in Brain-Computer Interfaces
... Inria / LaBRI Bordeaux, France fabien.lotte@inria.fr Abstract—The omnipresence of non-stationarity and noise in Electroencephalogram signals restricts the ubiquitous use of Brain-Computer interface. One of the ...
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Towards next generation human-computer interaction -- brain-computer interfaces: applications and challenges
... ABSTRACT Brain-computer interfaces (BCIs) are systems that record brain signals and transfer them into commands to build a di- rect communication pathway between a human brain and a ...
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Towards Adaptive Classification using Riemannian Geometry approaches in Brain-Computer Interfaces
... (EEG)-based Brain-Computer In- terfaces (BCIs) have proven promising for many applications, ranging from communication and control for severely motor- impaired users, entertainment, mental state monitoring to ...
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Optimizing the use of SSVEP-based brain-computer interfaces for human-computer interaction
... Selection involves choosing one or multiple elements from a set of fixed size (e.g. menus, radio buttons, checkboxes) or of variable size (e.g. 2D or 3D targeting, dropdown boxes, or selectboxes). Typically, selection ...
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Étude de corrélats électrophysiologiques pour la discrimination d'états de fatigue et de charge mentale : apports pour les interfaces cerveau-machine passives
... L'estimation de l'état mental d'un individu sur la base de son activité cérébrale et de ses ac- tivités physiologiques résultantes est devenue l'un des challenges des interfaces cerveau-machine (ICM) dites ...
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Interfaces Homme-Machine et Théorie du Regulatory Fit : les caractéristiques graphiques d’interfaces Homme-Machine comme moyen d’adapter l’orientation stratégique des utilisateurs au type de tâche
... preference judgment. Obviously, these findings lack of ecological validity. However, they represent, in our opinion, the first step towards more contextualized and natural researches on one hand, and a base for actual ...
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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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A Brain-Machine Interface for Control of Medically-Induced Coma
... profound brain inactivation and unconsciousness used to treat refractory intracranial hypertension and to manage treatment-resistant ...patient’s brain activity with an electroencephalogram (EEG) 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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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
... and machine learning from 2007 to 2017 in order to identify which new EEG classification algorithms have been investigated to design BCI, and which appear to be the most ...review machine learning methods ...
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Machine learning for classification and prediction of brain diseases: recent advances and upcoming challenges
... The most common use of ML is probably computer-assisted diagnosis. Early works have tackled automatic classification of Alzheimer’s disease [2,3] and schizophrenia [1] from anatomical MRI data. Since then, hundreds of ...
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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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