Emotion Recognition Based on a EEG–fNIRS Hybrid Brain Network in the Source Space
Mingxing Hou, Xueying Zhang, Guijun Chen, Lixia Huang, Ying Sun · 2024
Read Emotion Recognition Based on a EEG–fNIRS Hybrid Brain Network in the Source Space by Mingxing Hou, Xueying Zhang, Guijun Chen, Lixia Huang, Ying Sun (2024) in the Tower of Babel, a free online library of public-domain works preserved in clean, searchable text. No sign-up. The full text is served as a plain-text file at a predictable URL, where text is present: https://antarctic-labs.com/tower-of-babel/pmc-11674611.txt.
Description
Mingxing Hou and co-authors read emotions from combined brain signals in two thousand twenty-four. One method records electric waves from the scalp. Another tracks blood flow with near-infrared light. Together they beat either method alone for emotion reading. The team built hybrid brain networks in source space. Source space means signals are mapped back into the brain.
Electric signals were first localized to their brain sources. Causal networks traced influence between those sources. Coupled networks from the light signals were added. Merging both views gave a richer picture of emotion states. The method aims for finer emotion classification. It also exposes how the two signal types relate. Such hybrids may improve brain-computer interfaces for mood.
Catalog record
| CREATOR | Mingxing Hou, Xueying Zhang, Guijun Chen, Lixia Huang, Ying Sun |
|---|---|
| YEAR | 2024 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 39 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |