Covert Verb Reading Contributes to Signal Classification of Motor Imagery in BCI
- Submitting institution
-
Brunel University London
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 047-181501-14958
- Type
- D - Journal article
- DOI
-
10.1109/TNSRE.2017.2759241
- Title of journal
- Ieee Transactions On Neural Systems And Rehabilitation Engineering
- Article number
- -
- First page
- 45
- Volume
- 26
- Issue
- 1
- ISSN
- 1534-4320
- Open access status
- Compliant
- Month of publication
- October
- Year of publication
- 2017
- URL
-
https://bura.brunel.ac.uk/handle/2438/15685
- 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)
-
1 - Artificial Intelligence (AI)
- Citation count
- 1
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- The unique combination of semantic processing with motor imagery provides a novel way of improving the performance of BCI (Brain-Computer Interface) with wide applications including wheelchair, video games, virtual car and many others. This study established the long-term international research collaboration between myself and Tongji University, China. The results of this collaboration have led to further funding from the National Science Foundation, China and provided the basis for the continuation and development of the study, which resulted in a number of journal and conference publications, e.g., IEEE Access (2019) (https://doi.org/10.1109/ACCESS.2019.2904910) and NeuroComputing (2020) (https://doi.org/10.1016/j.neucom.2019.12.051).
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -
