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A Survey on the Use of Haptic Feedback for Brain-Computer Interfaces and Neurofeedback

Mathis Fleury, Giulia Lioi, Christian Barillot, Anatole Lécuyer

2020Frontiers in Neuroscience87 citationsDOIOpen Access PDF

Abstract

Neurofeedback (NF) and brain-computer interface (BCI) applications rely on the registration and real-time feedback of individual patterns of brain activity with the aim of achieving self-regulation of specific neural substrates or control of external devices. These approaches have historically employed visual stimuli. However, in some cases vision is unsuitable or inadequately engaging. Other sensory modalities, such as auditory or haptic feedback have been explored, and multisensory stimulation is expected to improve the quality of the interaction loop. Moreover, for motor imagery tasks, closing the sensorimotor loop through haptic feedback may be relevant for motor rehabilitation applications, as it can promote plasticity mechanisms. This survey reviews the various haptic technologies and describes their application to BCIs and NF. We identify major trends in the use of haptic interfaces for BCI and NF systems and discuss crucial aspects that could motivate further studies.

Topics & Concepts

Brain–computer interfaceHaptic technologyNeurofeedbackComputer scienceMotor imageryHuman–computer interactionModalitiesAuditory feedbackTask (project management)Interface (matter)RehabilitationPsychologyArtificial intelligenceNeuroscienceElectroencephalographyEngineeringSocial scienceSystems engineeringMaximum bubble pressure methodParallel computingBubbleSociologyEEG and Brain-Computer InterfacesNeuroscience and Neural EngineeringTactile and Sensory Interactions
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