An Eyewear-Based EEG Interface for Temporal-Region Monitoring and Emotion Recognition
Conventional electroencephalography (EEG) devices are often impractical for ambulatory settings due to their reliance on specialized hardware and expert operation. To address this, we developed a user-friendly eyewear-based EEG system featuring dry titanium electrodes positioned approximately 5 mm inferoposterior to the T7/T8 sites (near the ears), with metal nose pads serving as references. We evaluated the system across 103 recordings spanning five paradigms: alpha reactivity, blink-related transients, fatigue, attention, and video-elicited emotion. Following quality control, 93.2-100.0% of epochs were retained. The system demonstrated high sensitivity to ocular transients, showing significant amplitude increases during the blinking task. The emotion task yielded the most robust state-related features, with statistically significant differences in differential entropy across negative, neutral, and positive video categories, achieving balanced accuracies of 0.882 for two-class and 0.667 for three-class prediction. Despite challenges at the multiple testing correction stage, the alpha reactivity and fatigue contrast tasks were still noteworthy to some extent. The attention paradigm revealed a consistent increase in differential entropy during focused states, and the eyewear system outperformed the Muse headband in group-held-out classification. These findings provide strong evidence for the feasibility of temporal-region eyewear EEG acquisition, highlighting its potential applications in the real-world, particularly for emotion recognition.
Authors
- Xiaotao Li (ORCID: https://orcid.org/0000-0003-1598-1430)
- Lining Chai (ORCID: https://orcid.org/0009-0009-2040-8162)
- Jianguang Ni (ORCID: https://orcid.org/0000-0003-2023-9230)
- Kwok-Fai So
- Shen Xu
Institutions
- Jinan University (CN)
- Peking University (CN)
- Fudan University (CN)
- Education University of Hong Kong (HK)
- Huashan Hospital (CN)
Publication Details
- Journal
- bioRxiv (Cold Spring Harbor Laboratory)
- Published
- 2026-11-04
- DOI
- https://doi.org/10.64898/2026.11.02.763849
- Primary Topic
- EEG and Brain-Computer Interfaces
- Type
- preprint