AIMC Topic: Brain-Computer Interfaces

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A Feasibility Study of SSVEP-Based Passive Training on an Ankle Rehabilitation Robot.

Journal of healthcare engineering Sep 17, 2017
OBJECTIVE: This study aims to establish a steady-state visual evoked potential- (SSVEP-) based passive training protocol on an ankle rehabilitation robot and validate its feasibility.
Male Rehabilitation Brain-Computer Interfaces Virtual Reality Ankle Evoked Potentials, Visual Female Photic Stimulation Ankle Joint Robotics Reproducibility of Results Fourier Analysis Motion Young Adult Electroencephalography Healthy Volunteers Signal Processing, Computer-Assisted Feasibility Studies Humans Algorithms
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Towards Rehabilitation Robotics: Off-the-Shelf BCI Control of Anthropomorphic Robotic Arms.

BioMed research international Aug 29, 2017
Advances in neural interfaces have demonstrated remarkable results in the direction of replacing and restoring lost sensorimotor function in human patients. Noninvasive brain-computer interfaces (BCIs) are popular due to considerable advantages inclu...
Brain-Computer Interfaces Humans Rehabilitation Robotics Artificial Limbs Prosthesis Design
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Cognitive-Based EEG BCIs and Human Brain-Robot Interactions.

Computational intelligence and neuroscience Aug 28, 2017
Brain Robotics Electroencephalography Brain-Computer Interfaces Humans
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Parsing learning in networks using brain-machine interfaces.

Current opinion in neurobiology Aug 24, 2017
Brain-machine interfaces (BMIs) define new ways to interact with our environment and hold great promise for clinical therapies. Motor BMIs, for instance, re-route neural activity to control movements of a new effector and could restore movement to pe...
Humans Brain-Computer Interfaces Machine Learning Learning Animals Brain Neuronal Plasticity
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Transfer Learning: A Riemannian Geometry Framework With Applications to Brain-Computer Interfaces.

IEEE transactions on bio-medical engineering Aug 21, 2017
OBJECTIVE: This paper tackles the problem of transfer learning in the context of electroencephalogram (EEG)-based brain-computer interface (BCI) classification. In particular, the problems of cross-session and cross-subject classification are conside...
Brain-Computer Interfaces Humans Machine Learning Databases, Factual Models, Theoretical Electroencephalography
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Deep learning with convolutional neural networks for EEG decoding and visualization.

Human brain mapping Aug 7, 2017
Deep learning with convolutional neural networks (deep ConvNets) has revolutionized computer vision through end-to-end learning, that is, learning from the raw data. There is increasing interest in using deep ConvNets for end-to-end EEG analysis, but...
Brain Language Brain Mapping Humans Machine Learning Motor Activity Electroencephalography Space Perception Brain-Computer Interfaces Imagination Neural Pathways
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Virtual and Actual Humanoid Robot Control with Four-Class Motor-Imagery-Based Optical Brain-Computer Interface.

BioMed research international Jul 18, 2017
Motor-imagery tasks are a popular input method for controlling brain-computer interfaces (BCIs), partially due to their similarities to naturally produced motor signals. The use of functional near-infrared spectroscopy (fNIRS) in BCIs is still emergi...
Brain-Computer Interfaces Motor Activity Humans Visual Perception Male Adult Adolescent Robotics
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The impact of goal-oriented task design on neurofeedback learning for brain-computer interface control.

Medical & biological engineering & computing Jul 8, 2017
Neurofeedback training teaches individuals to modulate brain activity by providing real-time feedback and can be used for brain-computer interface control. The present study aimed to optimize training by maximizing engagement through goal-oriented ta...
Adult Male Electroencephalography Female Young Adult Functional Laterality Teaching Self Report Brain-Computer Interfaces Neurofeedback Humans Neural Networks, Computer Brain Learning
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Automated Classification and Removal of EEG Artifacts With SVM and Wavelet-ICA.

IEEE journal of biomedical and health informatics Jul 4, 2017
Brain electrical activity recordings by electroencephalography (EEG) are often contaminated with signal artifacts. Procedures for automated removal of EEG artifacts are frequently sought for clinical diagnostics and brain-computer interface applicati...
Artifacts Brain-Computer Interfaces Support Vector Machine Electroencephalography Signal Processing, Computer-Assisted Humans Brain
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Object Extraction in Cluttered Environments via a P300-Based IFCE.

Computational intelligence and neuroscience Jun 27, 2017
One of the fundamental issues for robot navigation is to extract an object of interest from an image. The biggest challenges for extracting objects of interest are how to use a machine to model the objects in which a human is interested and extract t...
Humans Robotics Color Lighting Brain-Computer Interfaces Event-Related Potentials, P300
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