AIMC Topic: Brain-Computer Interfaces

Clear Filters Showing 341 to 350 of 661 articles

EEG based Classification of Long-term Stress Using Psychological Labeling.

Sensors (Basel, Switzerland) Mar 29, 2020
Stress research is a rapidly emerging area in the field of electroencephalography (EEG) signal processing. The use of EEG as an objective measure for cost effective and personalized stress management becomes important in situations like the nonavaila...
Humans Machine Learning Algorithms Female Young Adult Adult Brain-Computer Interfaces Support Vector Machine Electroencephalography Signal Processing, Computer-Assisted Male Stress, Psychological
View on PubMed DOI

Brain-Controlled Robotic Arm System Based on Multi-Directional CNN-BiLSTM Network Using EEG Signals.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society Mar 18, 2020
Brain-machine interfaces (BMIs) can be used to decode brain activity into commands to control external devices. This paper presents the decoding of intuitive upper extremity imagery for multi-directional arm reaching tasks in three-dimensional (3D) e...
Movement Humans Robotics Brain Electroencephalography Brain-Computer Interfaces
View on PubMed DOI

Challenge Accepted? Individual Performance Gains for Motor Imagery Practice with Humanoid Robotic EEG Neurofeedback.

Sensors (Basel, Switzerland) Mar 14, 2020
Optimizing neurofeedback (NF) and brain-computer interface (BCI) implementations constitutes a challenge across many fields and has so far been addressed by, among others, advancing signal processing methods or predicting the user's control ability f...
Sensorimotor Cortex Neurofeedback Imagery, Psychotherapy Male Robotics Electroencephalography Signal Processing, Computer-Assisted Brain-Computer Interfaces Female Young Adult Adult Humans
View on PubMed DOI

Double-Criteria Active Learning for Multiclass Brain-Computer Interfaces.

Computational intelligence and neuroscience Mar 10, 2020
Recent technological advances have enabled researchers to collect large amounts of electroencephalography (EEG) signals in labeled and unlabeled datasets. It is expensive and time consuming to collect labeled EEG data for use in brain-computer interf...
Electroencephalography Brain-Computer Interfaces Humans Machine Learning
View on PubMed DOI

An empirical comparison of neural networks and machine learning algorithms for EEG gait decoding.

Scientific reports Mar 9, 2020
Previous studies of Brain Computer Interfaces (BCI) based on scalp electroencephalography (EEG) have demonstrated the feasibility of decoding kinematics for lower limb movements during walking. In this computational study, we investigated offline dec...
Humans Neural Networks, Computer Gait Brain-Computer Interfaces Machine Learning Algorithms Electroencephalography
View on PubMed DOI

A neural network for online spike classification that improves decoding accuracy.

Journal of neurophysiology Feb 26, 2020
Separating neural signals from noise can improve brain-computer interface performance and stability. However, most algorithms for separating neural action potentials from noise are not suitable for use in real time and have shown mixed effects on dec...
Neural Networks, Computer Brain-Computer Interfaces Electrocorticography Macaca mulatta Prefrontal Cortex Spatial Memory Animals Action Potentials Saccades Male Pattern Recognition, Automated
View on PubMed DOI

fNIRS-GANs: data augmentation using generative adversarial networks for classifying motor tasks from functional near-infrared spectroscopy.

Journal of neural engineering Feb 19, 2020
OBJECTIVE: Functional near-infrared spectroscopy (fNIRS) is expected to be applied to brain-computer interface (BCI) technologies. Since lengthy fNIRS measurements are uncomfortable for participants, it is difficult to obtain enough data to train cla...
Young Adult Adult Male Neural Networks, Computer Female Brain-Computer Interfaces Movement Motor Cortex Spectroscopy, Near-Infrared Support Vector Machine Psychomotor Performance Humans
View on PubMed DOI

Mental state space visualization for interactive modeling of personalized BCI control strategies.

Journal of neural engineering Feb 18, 2020
OBJECTIVE: Numerous studies in the area of BCI are focused on the search for a better experimental paradigm-a set of mental actions that a user can evoke consistently and a machine can discriminate reliably. Examples of such mental activities are mot...
Mental Processes Humans Electroencephalography Machine Learning Facial Expression Brain-Computer Interfaces
View on PubMed DOI

Dynamic time warping-based transfer learning for improving common spatial patterns in brain-computer interface.

Journal of neural engineering Feb 18, 2020
OBJECTIVE: Common spatial patterns (CSP) is a prominent feature extraction algorithm in motor imagery (MI)-based brain-computer interfaces (BCIs). However, CSP is computed using sample-based covariance-matrix estimation. Hence, its performance deteri...
Humans Signal Processing, Computer-Assisted Machine Learning Brain-Computer Interfaces Imagination Databases, Factual Electroencephalography
View on PubMed DOI

Reconstruction of natural visual scenes from neural spikes with deep neural networks.

Neural networks : the official journal of the International Neural Network Society Feb 8, 2020
Neural coding is one of the central questions in systems neuroscience for understanding how the brain processes stimulus from the environment, moreover, it is also a cornerstone for designing algorithms of brain-machine interface, where decoding inco...
Visual Cortex Animals Neural Networks, Computer Evoked Potentials, Visual Models, Neurological Magnetic Resonance Imaging Visual Perception Retinal Ganglion Cells Brain-Computer Interfaces
View on PubMed DOI
Popular Topics
Recent Journals