دورية أكاديمية
TBEEG: A Two-Branch Manifold Domain Enhanced Transformer Algorithm for Learning EEG Decoding
| العنوان: | TBEEG: A Two-Branch Manifold Domain Enhanced Transformer Algorithm for Learning EEG Decoding |
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| المؤلفون: | Yanjun Qin, Wenqi Zhang, Xiaoming Tao |
| المصدر: | IEEE Transactions on Neural Systems and Rehabilitation Engineering, Vol 32, Pp 1466-1476 (2024) |
| بيانات النشر: | IEEE, 2024. |
| سنة النشر: | 2024 |
| المجموعة: | LCC:Medical technology LCC:Therapeutics. Pharmacology |
| مصطلحات موضوعية: | EEG decoding, EEG signals, Riemannian spaces, spatial-temporal information, Medical technology, R855-855.5, Therapeutics. Pharmacology, RM1-950 |
| الوصف: | The electroencephalogram-based (EEG) brain-computer interface (BCI) has garnered significant attention in recent research. However, the practicality of EEG remains constrained by the lack of efficient EEG decoding technology. The challenge lies in effectively translating intricate EEG into meaningful, generalizable information. EEG signal decoding primarily relies on either time domain or frequency domain information. There lacks a method capable of simultaneously and effectively extracting both time and frequency domain features, as well as efficiently fuse these features. Addressing these limitations, a two-branch Manifold Domain enhanced transformer algorithm is designed to holistically capture EEG’s spatio-temporal information. Our method projects the time-domain information of EEG signals into the Riemannian spaces to fully decode the time dependence of EEG signals. Using wavelet transform, the time domain information is converted into frequency domain information, and the spatial information contained in the frequency domain information of EEG signal is mined through the spectrogram. The effectiveness of the proposed TBEEG algorithm is validated on BCIC-IV-2a dataset and MAMEM-SSVEP-II datasets. |
| نوع الوثيقة: | article |
| وصف الملف: | electronic resource |
| اللغة: | English |
| تدمد: | 1558-0210 |
| Relation: | https://ieeexplore.ieee.org/document/10478019/; https://doaj.org/toc/1558-0210 |
| DOI: | 10.1109/TNSRE.2024.3380595 |
| URL الوصول: | https://doaj.org/article/0da6e0d7c8e7441cb42de09b566a447f |
| رقم الأكسشن: | edsdoj.0da6e0d7c8e7441cb42de09b566a447f |
| قاعدة البيانات: | Directory of Open Access Journals |
Full Text Finder | تدمد: | 15580210 |
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| DOI: | 10.1109/TNSRE.2024.3380595 |