Advancing passive BCIs: a feasibility study of two temporal derivative features and effect size-based feature selection in continuous online EEG-based machine error detection
- DOI
- 10.3389/fnrgo.2024.1346791
- Published
- 2024-05-15
- Container
- Frontiers in Neuroergonomics
- Publisher
- Frontiers Media SA
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.3389/fnrgo.2024.1346791,
title = {Advancing passive BCIs: a feasibility study of two temporal derivative features and effect size-based feature selection in continuous online EEG-based machine error detection},
author = {Yanzhao Pan and Thorsten O. Zander and Marius Klug},
year = {2024},
journal = {Frontiers in Neuroergonomics},
doi = {10.3389/fnrgo.2024.1346791},
url = {https://doi.org/10.3389/fnrgo.2024.1346791}
}RIS
TY - JOUR TI - Advancing passive BCIs: a feasibility study of two temporal derivative features and effect size-based feature selection in continuous online EEG-based machine error detection AU - Yanzhao Pan AU - Thorsten O. Zander AU - Marius Klug PY - 2024 JO - Frontiers in Neuroergonomics DO - 10.3389/fnrgo.2024.1346791 UR - https://doi.org/10.3389/fnrgo.2024.1346791 ER -
APA
Pan, Y., Zander, T. O., & Klug, M. (2024). Advancing passive BCIs: a feasibility study of two temporal derivative features and effect size-based feature selection in continuous online EEG-based machine error detection. Frontiers in Neuroergonomics. https://doi.org/10.3389/fnrgo.2024.1346791
Source records
- crossref · retrieved 2026-09-25T21:49:58.311Z