Search results for "Brain–computer interface"

showing 10 items of 35 documents

Brain Synchrony in Competition and Collaboration During Multiuser Neurofeedback-Based Gaming

2021

EEG hyperscanning during multiuser gaming offers opportunities to study brain characteristics of social interaction under various paradigms. In this study, we aimed to characterize neural signatures and phase-based functional connectivity patterns of gaming strategies during collaborative and competitive alpha neurofeedback games. Twenty pairs of participants with no close relationship took part in three sessions of collaborative or competitive multiuser neurofeedback (NF), with identical graphical user interface, using Relative Alpha (RA) power as a control signal. Collaborating dyads had to keep their RA within 5% of each other for the team to be awarded a point, while members of competit…

Resting state fMRIfunctional connectivityComputingMilieux_PERSONALCOMPUTINGCognitionHyperconnectivityneurofeedbackSocial relationSocial exchange theoryEEGNeurology. Diseases of the nervous systemNeurofeedbackBCIphase locking value (PLV)PsychologyRC346-429hyperscanningCognitive psychologyDyadBrain–computer interfaceFrontiers in Neuroergonomics
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A BCI Teleoperated Museum Robotic Guide

2009

Brain Computer Interface is a system that offers also a support to the patients with neuromuscular diseases as Amyotrophic Lateral Sclerosis. In this paper are presented some works with the aim to integrate brain computer interfaces and mobile robots. The two aim of this project are: (i) to test an improved BCI experience through the help of a physical robot, so that brain signals are stronger stimulate. (ii) to use a remote robot controlled by a highly paralyzed patient via a BCI through a friendly Graphic User. Some preliminary experiments are presented in this paper about one of the possible application: a robotic museum guide (PeopleBot and Pioneer3 robot), that can transmit remote visu…

Settore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniMultimediaComputer sciencebusiness.industryMobile computingMobile robotcomputer.software_genreHuman–robot interactionRobot controlHuman–computer interactionAssistive Devices/Technology Human Robot InterfaceTeleoperationRobotbusinesscomputerBrain–computer interfaceGraphical user interface2009 International Conference on Complex, Intelligent and Software Intensive Systems
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Novel Human-to-Human Interactions from the Evolution of HCI

2011

The interaction ways made available by the evolution of the human-computer interfaces, led to novel Human-to-Human Interaction (HHI) modes, enabling people to cooperate for almost any task any time and any where. HHI nowadays is largely indirect and mediated by a wide variety of technologies and devices. This new and exciting field of design originates from the convergence of a few well-established research fields within the HCI area, such as traditional Graphical User Interfaces (GUI), Tangible User Interfaces (TUI), Touchless Gesture User Interface (TGUI), Voice User Interfaces (VUI), and Brain Computer Interfaces (BCI). We analyze and describe the evolution of the HCI in those fields, an…

Settore ING-INF/05 - Sistemi Di Elaborazione Delle Informazionihuman-to-human interactionMultimediaComputer sciencebusiness.industryPost-WIMPmediated social interactionscomputer.software_genreField (computer science)Variety (cybernetics)novel interfacehuman-computer interactionHuman–computer interactionHuman interactionUser interfacebusinesscomputerBrain–computer interfaceGraphical user interfaceGesture2011 International Conference on Complex, Intelligent, and Software Intensive Systems
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Human-to-human interfaces: emerging trends and challenges

2011

We present a new research domain, human-to-human interaction (HHI) that describes how today's human interaction is largely indirect and mediated by a wide variety of technologies and devices. We show how this new and exciting field of design originates from the convergence of a few well-established research areas, such as traditional graphical user interfaces (GUIs), tangible user interfaces (TUIs), touchless gesture user interfaces (TGUIs), voice user interfaces (VUIs), and brain computer interfaces (BCIs). We analyse and describe current research in those areas and offer a first-hand view and presentation of its salient aspects for the human-to human interaction domain.

Settore ING-INF/05 - Sistemi Di Elaborazione Delle Informazionihuman-to-human interactionMultimediabusiness.industryComputer scienceHHIhuman-to-human interfacePost-WIMPcomputer.software_genreField (computer science)Variety (cybernetics)Domain (software engineering)Human–computer interactionUser interfacebusinesscomputerhuman-to-computer interfacesGraphical user interfaceBrain–computer interfaceGesture
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P300-based brain computer interface experimental setup

2009

A Brain-Computer interface (BCI) is a communication system that enables the generation of a control signal from brain signals such as sensorymotor rhythms and evoked potentials; therefore, it constitutes a novel communication option for people with severe motor disabilities (such as Amyotrophic Lateral Sclerosis patients). This paper presents the development of a P300-based BCI. This prototype uses a homemade six-channel electroencephalograph for the acquisition of the signals, and a visual stimulation matrix; since this matrix contains letters of the alphabet as well as images associated to them, it permits word-writing and the elaboration of messages with the images. To process the signal…

Signal processingmedicine.diagnostic_testComputer scienceSpeech recognitionInterface (computing)BrainReproducibility of ResultsElectroencephalographyElectroencephalographyLinear discriminant analysisEvent-Related Potentials P300Sensitivity and SpecificityLeast squaresUser-Computer InterfacePattern Recognition VisualmedicineAlgorithmsVisual CortexBrain–computer interface2009 Annual International Conference of the IEEE Engineering in Medicine and Biology Society
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Brain Controlled Architecture for Human-Human Interaction Mediated by a Humanoid Robot

2017

This paper presents an Assistive social robots architecture designed for social interaction with humans, mediated by a humanoid robot. The architecture has been designed for being used by people with severe paralysis and the architecture has been tested by a user affected by amyotrophic lateral sclerosis (ALS) in a locked-in state. The system allows the patient to communicate with the stakeholders using a Brain Controlled Interface, based on Evoked Response Potentials (ERP), to express needing, feelings or writing phases. Stakeholders visualize messages sent by the patient on a GUI and use a tele operated humanoid robot as an avatar of them to extend their physical presence to interact with…

Social robotAssistive RoboticComputer scienceInterface (computing)Brain Computer InterfaceBrain Computer Interface; Social Robotics; Assistive Robotics; Architecture; EEG; ERP; Human-Humanoid InteractionCommunications systemHuman–robot interactionHuman–computer interactionArchitectureRobotHuman-Humanoid InteractionEEGSocial RoboticERPHumanoid robotBrain–computer interfaceAvatarInternational Robotics & Automation Journal
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Development of the BCI Device Controlling C++ Software, Based on Existing Open Source Projects

2021

The possibility of using the BCI open source code for building BCI controlled device, based on small AVR or ARM microcontrollers was considered. Some techniques to extract code snippets from other BCI projects were presented in the case of OpenViBE as the code donor. Problem with obtaining driver source codes for factory BCI devices has been pointed out.

Source codeOpenVibeInformationSystems_INFORMATIONINTERFACESANDPRESENTATION(e.g.HCI)Computer sciencebusiness.industrymedia_common.quotation_subjectBCI driversMicrocontrollerInformationSystems_MODELSANDPRINCIPLESSoftwareDevelopment (topology)BCI softwareEmbedded systemCode (cryptography)Factory (object-oriented programming)BCIbusinessBrain–computer interfacemedia_common
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Simplified spiking neural network architecture and STDP learning algorithm applied to image classification

2015

Spiking neural networks (SNN) have gained popularity in embedded applications such as robotics and computer vision. The main advantages of SNN are the temporal plasticity, ease of use in neural interface circuits and reduced computation complexity. SNN have been successfully used for image classification. They provide a model for the mammalian visual cortex, image segmentation and pattern recognition. Different spiking neuron mathematical models exist, but their computational complexity makes them ill-suited for hardware implementation. In this paper, a novel, simplified and computationally efficient model of spike response model (SRM) neuron with spike-time dependent plasticity (STDP) lear…

Spiking neural networkQuantitative Biology::Neurons and CognitionComputational complexity theoryContextual image classificationComputer sciencebusiness.industryImage segmentationNetwork topologyExternal Data RepresentationSignal ProcessingArtificial neuronArtificial intelligenceElectrical and Electronic EngineeringbusinessInformation SystemsBrain–computer interfaceEURASIP Journal on Image and Video Processing
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Evaluating the Effect of Stimuli Color and Frequency on SSVEP

2020

Brain&ndash

Visual perceptionBrain-Computer InterfaceFrequency bandSpeech recognitionbiomedical signal processingLow frequencyStimulus (physiology)Electroencephalographylcsh:Chemical technology01 natural sciencesBiochemistryRed ColorArticleAnalytical Chemistry03 medical and health sciences0302 clinical medicineContinuous performance taskmedicinelcsh:TP1-1185Electrical and Electronic EngineeringInstrumentationSSVEPBrain–computer interfaceMathematicsmedicine.diagnostic_test010401 analytical chemistrybrain–computer interfaceAtomic and Molecular Physics and Optics0104 chemical sciences030217 neurology & neurosurgeryelectroencephalographySensors
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Editorial: Breakthrough BCI Applications in Medicine

2020

medicine.diagnostic_testComputer scienceGeneral NeuroscienceSpeech recognitionElectroencephalographyclinical applicationslcsh:RC321-571EditorialMotor imagerymotor imagerymedicineEEGBCIP300lcsh:Neurosciences. Biological psychiatry. NeuropsychiatryNeuroscienceBrain–computer interfaceFrontiers in Neuroscience
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