Alertness assessment by optical stimulation-induced brainwave entrainment through machine learning classification
Our study demonstrated that the use of machine learning to integrate EEG features during 30 s optical stimulation-induced BWE showed promising classification capabilities for alertness states. It provided a rapid, quantifiable, and easily implementable alertness assessment option.
Authors
- Zhou Yong (ORCID: https://orcid.org/0000-0002-0898-162X)
- Hanshu Cai (ORCID: https://orcid.org/0000-0002-8918-0591)
- Yizhou Tan
- Ying Gu (ORCID: https://orcid.org/0000-0002-1729-2092)
- Shasha Wang (ORCID: https://orcid.org/0000-0001-5270-5828)
Institutions
- Chinese PLA General Hospital (CN)
- Hainan General Hospital (CN)
- Hainan 301 Hospital (CN)
- Chinese People's Liberation Army (CN)
- Chinese People’s Liberation Army 263 hospital (CN)
- Lanzhou University (CN)
Publication Details
- Journal
- BioMedical Engineering OnLine
- Published
- 2025-08-12
- DOI
- https://doi.org/10.1186/s12938-025-01422-4
- Primary Topic
- EEG and Brain-Computer Interfaces
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China
- National Key Research and Development Program of China