Predicting workload profiles of brain-robot interface and electromygraphic neurofeedback with cortical resting-state networks: personal trait or task-specific challenge?
Identifieur interne : 003A85 ( Ncbi/Curation ); précédent : 003A84; suivant : 003A86Predicting workload profiles of brain-robot interface and electromygraphic neurofeedback with cortical resting-state networks: personal trait or task-specific challenge?
Auteurs : Meike Fels ; Robert Bauer ; Alireza GharabaghiSource :
- Journal of neural engineering [ 1741-2552 ] ; 2015.
English descriptors
- KwdEn :
- Adult, Brain-Computer Interfaces, Cerebral Cortex (physiology), Electromyography (methods), Female, Humans, Male, Middle Aged, Nerve Net (physiology), Neurofeedback (methods), Physical Exertion (physiology), Psychomotor Performance (physiology), Rest (physiology), Robotics (methods), Workload, Young Adult.
- MESH :
- methods : Electromyography, Neurofeedback, Robotics.
- physiology : Cerebral Cortex, Nerve Net, Physical Exertion, Psychomotor Performance, Rest.
- Adult, Brain-Computer Interfaces, Female, Humans, Male, Middle Aged, Workload, Young Adult.
Abstract
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 interventions and the related cortical activation patterns.
DOI: 10.1088/1741-2560/12/4/046029
PubMed: 26170164
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pubmed:26170164Le document en format XML
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