AIMC Topic: Brain-Computer Interfaces

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The Cybathlon BCI race: Successful longitudinal mutual learning with two tetraplegic users.

PLoS biology May 10, 2018
This work aims at corroborating the importance and efficacy of mutual learning in motor imagery (MI) brain-computer interface (BCI) by leveraging the insights obtained through our participation in the BCI race of the Cybathlon event. We hypothesized ...
Learning Brain-Computer Interfaces Quadriplegia Humans Machine Learning
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A fresh look at functional link neural network for motor imagery-based brain-computer interface.

Journal of neuroscience methods May 4, 2018
BACKGROUND: Artificial neural networks (ANNs) are one of the widely used classifiers in the brain-computer interface (BCI) systems-based on noninvasive electroencephalography (EEG) signals. Among the different ANN architectures, the most commonly app...
Humans Neural Networks, Computer Brain Support Vector Machine Linear Models Brain-Computer Interfaces Motor Activity Imagination Bayes Theorem Electroencephalography Signal Processing, Computer-Assisted
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Control of a 7-DOF Robotic Arm System With an SSVEP-Based BCI.

International journal of neural systems Apr 12, 2018
Although robot technology has been successfully used to empower people who suffer from motor disabilities to increase their interaction with their physical environment, it remains a challenge for individuals with severe motor impairment, who do not h...
Humans Brain Female Brain-Computer Interfaces Evoked Potentials, Visual Photic Stimulation Wireless Technology Eye Movements Electroencephalography Pattern Recognition, Visual Young Adult Robotics Attention Adult Male
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Motor Imagery-Based Brain-Computer Interface Coupled to a Robotic Hand Orthosis Aimed for Neurorehabilitation of Stroke Patients.

Journal of healthcare engineering Apr 3, 2018
Motor imagery-based brain-computer interfaces (BCI) have shown potential for the rehabilitation of stroke patients; however, low performance has restricted their application in clinical environments. Therefore, this work presents the implementation o...
Stroke Rehabilitation Female Imagination Aged Young Adult Electroencephalography Humans Adult Male Signal Processing, Computer-Assisted Algorithms Hand Middle Aged Brain-Computer Interfaces Robotics
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Relevant Feature Selection from a Combination of Spectral-Temporal and Spatial Features for Classification of Motor Imagery EEG.

Journal of medical systems Mar 16, 2018
This paper presents a novel algorithm (CVSTSCSP) for determining discriminative features from an optimal combination of temporal, spectral and spatial information for motor imagery brain computer interfaces. The proposed method involves four phases. ...
Humans Algorithms Brain-Computer Interfaces Support Vector Machine Electroencephalography Signal Processing, Computer-Assisted
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Learning Temporal Information for Brain-Computer Interface Using Convolutional Neural Networks.

IEEE transactions on neural networks and learning systems Mar 9, 2018
Deep learning (DL) methods and architectures have been the state-of-the-art classification algorithms for computer vision and natural language processing problems. However, the successful application of these methods in motor imagery (MI) brain-compu...
Brain-Computer Interfaces Imagination Electroencephalography Signal Processing, Computer-Assisted Pattern Recognition, Automated Humans Brain Learning Neural Networks, Computer Algorithms
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Deep learning for hybrid EEG-fNIRS brain-computer interface: application to motor imagery classification.

Journal of neural engineering Feb 15, 2018
OBJECTIVE: Brain-computer interface (BCI) refers to procedures that link the central nervous system to a device. BCI was historically performed using electroencephalography (EEG). In the last years, encouraging results were obtained by combining EEG ...
Humans Acoustic Stimulation Movement Motor Cortex Deep Learning Imagination Adult Electroencephalography Male Psychomotor Performance Spectroscopy, Near-Infrared Brain-Computer Interfaces
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fNIRS-based Neurorobotic Interface for gait rehabilitation.

Journal of neuroengineering and rehabilitation Feb 5, 2018
BACKGROUND: In this paper, a novel functional near-infrared spectroscopy (fNIRS)-based brain-computer interface (BCI) framework for control of prosthetic legs and rehabilitation of patients suffering from locomotive disorders is presented.
Exoskeleton Device Neurological Rehabilitation Discriminant Analysis Artificial Limbs Brain-Computer Interfaces Spectroscopy, Near-Infrared Support Vector Machine Robotics Adult Male Humans
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A Biologically Inspired Approach to Frequency Domain Feature Extraction for EEG Classification.

Computational and mathematical methods in medicine Jan 23, 2018
Classification of electroencephalogram (EEG) signal is important in mental decoding for brain-computer interfaces (BCI). We introduced a feature extraction approach based on frequency domain analysis to improve the classification performance on diffe...
Support Vector Machine Electroencephalography Signal Processing, Computer-Assisted Imagination Brain-Computer Interfaces Movement Algorithms Brain Female Humans
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Emergent coordination underlying learning to reach to grasp with a brain-machine interface.

Journal of neurophysiology Dec 13, 2017
The development of coordinated reach-to-grasp movement has been well studied in infants and children. However, the role of motor cortex during this development is unclear because it is difficult to study in humans. We took the approach of using a bra...
Conditioning, Operant Psychomotor Performance Brain-Computer Interfaces Artificial Limbs Behavior, Animal Motor Activity Motor Cortex Female Neurons Amputation, Surgical Macaca mulatta Animals Arm Robotics
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