Linear SVM algorithm optimization for an EEG-based brain-computer interface used by high functioning autism spectrum disorder participants
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ID-4's best performing parameter setting resulted in a customized solution per participant and per session.
“In the last attempt, the best performing parameter setting was selected, resulting in a customized solution per participant and per session.”
From BCIAUT-P300: A Multi-Session and Multi-Subject Benchmark Dataset on Autism for P300-Based Brain-Computer-Interfaces (2020) · cites this paper as Bittencourt-Villalpando and Maurits, 2020
Cites
Amaral, C., Mouga, S., Simões, M., Pereira, H. C., Bernardino, I., Quental, H., Playle, R., McNamara, R., Oliveira, G., & Castelo-Branco, M. (2018) · Frontiers in Neuroscience · doi:10.3389/fnins.2018.00477 · Cited by 94 · see citing works
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Simões, M., Borra, D., Santamaría-Vázquez, E., GBT-UPM, Bittencourt-Villalpando, M., Krzemiński, D., Miladinović, A., Neural_Engineering_Group, Schmid, T., Zhao, H., et al. (2020) · Frontiers in Neuroscience · doi:10.3389/fnins.2020.568104 · Cited by 72 · see citing works
Self-citation
- Authors
- Bittencourt-Villalpando, M., & Maurits, N. M.
- Affiliations
- University Medical Center Groningen (NL)
- Corresponding author
- Bittencourt-Villalpando, Mayra
- Venue
- IFMBE Proceedings
- Publisher
- Springer International Publishing
- Published
- 2019-09-25
- Pages
- 1875-1884
- ISSN
- 1433-9277 (ISSN-L)
- 1680-0737
- OpenAlex
- W2975206125
- Cited by
- 8
- References
- 1
- Citations by year
- 2025: 2 · 2023: 1 · 2022: 3 · 2021: 1 · 2020: 1
- FWCI
- 2.15
- Type
- conference paper
- Language
- en
- Open access
- green
- hdl.handle.net
- Licence
- other-oa
- www.springer.com/tdm (tdm)
- Locations
- World Congress on Medical Physics and Biomedical Engineering, September 7 - 12, 2009, Munich, Germany (publishedVersion)
- University of Groningen research database (University of Groningen / Centre for Information Technology) (submittedVersion, other-oa)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › EEG and Brain-Computer Interfaces
- Physical Sciences › Computer Science › Human-Computer Interaction › Gaze Tracking and Assistive Technology
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Emotion and Mood Recognition
- Keywords
- brain-computer interface, autism spectrum disorder, P300, linear support vector machine, EEG classification, parameter optimization, calibration data, attention training
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
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