EEG-based mobile robot control through an adaptive brain–robot interface
- Submitting institution
-
Middlesex University
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 1494
- Type
- D - Journal article
- DOI
-
10.1109/TSMC.2014.2313317
- Title of journal
- IEEE Transactions on Systems Man and Cybernetics: Systems
- Article number
- -
- First page
- 1278
- Volume
- 44
- Issue
- 9
- ISSN
- 2168-2216
- Open access status
- Out of scope for open access requirements
- Month of publication
- April
- Year of publication
- 2014
- URL
-
http://eprints.mdx.ac.uk/13694/
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
-
4
- Research group(s)
-
-
- Citation count
- 47
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- A major challenge in two-class brain-computer interface (BCI) systems is that the user can only send one of two commands at any time. This poses a challenge when controlling assistive devices (wheelchair/robot) requiring multiple motion command options as forward/left/right/backward/start/stop. The paper is significant because it describes an intelligent adaptive user interface (iAUI) based on an adaptive shared control mechanism. The iAUI offers control of a robotic device by providing a continuously updated prioritized list of all the options for selection to the BCI user. Results have been verified with multiple participants controlling a simulated as well as physical robot.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -