STAFNet: an adaptive multi-feature learning network via spatiotemporal fusion for EEG-based emotion recognition
In summary, the findings validate the effectiveness of STAFNet in EEG-based emotion recognition. The results emphasize the critical role of spatiotemporal feature extraction and introduce an innovative framework for feature fusion, advancing the state of the art in emotion recognition.
Authors
- Mengyuan Qian
- Fo Hu (ORCID: https://orcid.org/0000-0003-2497-9623)
- Lekai Zhang (ORCID: https://orcid.org/0000-0002-8136-5882)
- Xiaofeng Liu (ORCID: https://orcid.org/0000-0001-5024-9187)
- Zukang Qiao (ORCID: https://orcid.org/0000-0003-4782-6785)
- Kailun He (ORCID: https://orcid.org/0009-0001-6556-4558)
- Junwu Xiong (ORCID: https://orcid.org/0009-0008-8508-9011)
Institutions
- Zhejiang Chinese Medical University (CN)
- Zhejiang University of Technology (CN)
Publication Details
- Journal
- Frontiers in Neuroscience
- Published
- 2024-12-10
- DOI
- https://doi.org/10.3389/fnins.2024.1519970
- Citations
- 3
- Primary Topic
- EEG and Brain-Computer Interfaces
- Type
- article
- Field-Weighted Citation Impact
- 1.03