FORCe: Fully Online and Automated Artifact Removal for Brain-Computer Interfacing.
- Submitting institution
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The University of Essex
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 1166
- Type
- D - Journal article
- DOI
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10.1109/tnsre.2014.2346621
- Title of journal
- IEEE Transactions on Neural Systems and Rehabilitation Engineering
- Article number
- -
- First page
- 725
- Volume
- 23
- Issue
- 5
- ISSN
- 1534-4320
- Open access status
- Out of scope for open access requirements
- Month of publication
- August
- Year of publication
- 2014
- URL
-
-
- 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
- Yes
- Number of additional authors
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3
- Research group(s)
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B - Brain Computer Interfaces and Neural Engineering (BCI-NE)
- Citation count
- 68
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- Originality: This paper builds upon highly-cited work in IEEE Transactions by Daly et.al. It describes a state-of-the-art automated artefact removal tool for brain-computer interfaces.
Significance: With over 3700 full-text reads, this is a widely-applied paper. Code is available and has multiple uses, including for individuals with Cerebral Palsy (Scherer, Austria), hybrid-BCIs (Hong, South Korea), and motor-BCIs (Meinel, Germany). It also impacts neuroscience, including epileptic seizure detection (Abreu, Portugal) and vigilance measurement (Zheng, China).
Rigour: The method was tested with a large patient population and validated during sets of online BCI experiments. State-of-the-art analysis methods and blinded artefact labelling were applied.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -