AIMC Topic: Neurofeedback

Clear Filters Showing 21 to 25 of 25 articles

Predicting workload profiles of brain-robot interface and electromygraphic neurofeedback with cortical resting-state networks: personal trait or task-specific challenge?

Journal of neural engineering
OBJECTIVE: Novel rehabilitation strategies apply robot-assisted exercises and neurofeedback tasks to facilitate intensive motor training. We aimed to disentangle task-specific and subject-related contributions to the perceived workload of these inter...

EEG decoding with spatiotemporal convolutional neural network for visualization and closed-loop control of sensorimotor activities: A simultaneous EEG-fMRI study.

Human brain mapping
Closed-loop neurofeedback training utilizes neural signals such as scalp electroencephalograms (EEG) to manipulate specific neural activities and the associated behavioral performance. A spatiotemporal filter for high-density whole-head scalp EEG usi...

A TrAdaBoost Method for Detecting Multiple Subjects' N200 and P300 Potentials Based on Cross-Validation and an Adaptive Threshold.

International journal of neural systems
Traditional training methods need to collect a large amount of data for every subject to train a subject-specific classifier, which causes subjects fatigue and training burden. This study proposes a novel training method, TrAdaBoost based on cross-va...

Dynamic feature selection applied to the recognition of grasping movements in the control of bioprosthetic hand.

Studies in health technology and informatics
The paper presents novel method of dynamic feature selection (DFS) and its application in the problem of recognition of patient intent in the bioprosthesis control system. In the proposed approach features are selected dynamically, i.e. separately fo...