Motor imagery for severely motor-impaired patients: evidence for brain-computer interfacing as superior control solution.
Brain-Computer Interfaces (BCIs) strive to decode brain signals into control commands for severely handicapped people with no means of muscular control. These potential users of noninvasive BCIs display a large range of physical and mental conditions. Prior studies have shown the general applicabili...
Enregistré dans:
Auteurs principaux: | Johannes Höhne, Elisa Holz, Pit Staiger-Sälzer, Klaus-Robert Müller, Andrea Kübler, Michael Tangermann |
---|---|
Format: | article |
Langue: | EN |
Publié: |
Public Library of Science (PLoS)
2014
|
Sujets: | |
Accès en ligne: | https://doaj.org/article/d01b9a6d62b24dc59058fc29d74d2783 |
Tags: |
Ajouter un tag
Pas de tags, Soyez le premier à ajouter un tag!
|
Documents similaires
-
Characterization of kinesthetic motor imagery compared with visual motor imageries
par: Yu Jin Yang, et autres
Publié: (2021) -
A co-adaptive brain-computer interface for end users with severe motor impairment.
par: Josef Faller, et autres
Publié: (2014) -
Prediction of P300 BCI aptitude in severe motor impairment.
par: Sebastian Halder, et autres
Publié: (2013) -
A magnetoencephalography dataset for motor and cognitive imagery-based brain-computer interface
par: Dheeraj Rathee, et autres
Publié: (2021) -
The Differences Between Motor Attempt and Motor Imagery in Brain-Computer Interface Accuracy and Event-Related Desynchronization of Patients With Hemiplegia
par: Shugeng Chen, et autres
Publié: (2021)