Name
Abstract | ||
|---|---|---|
Visual evoked potential (VEP)-related EEG signals have attracted widespread attention in the construction of brain-computer interface (BCI) systems. However, long-term use of the BCI system is prone to fatigue. Effectively coping with fatigue is the key to expanding BCI application scenarios. In this brief, we conduct two VEP experiments and propose a novel, concise and practical convolutional neu... |
Year | DOI | Venue |
|---|---|---|
2022 | 10.1109/TCSII.2021.3091803 | IEEE Transactions on Circuits and Systems II: Express Briefs |
Keywords | DocType | Volume |
Brain modeling,Fatigue,Harmonic analysis,Electroencephalography,Couplings,Visualization,Feature extraction | Journal | 69 |
Issue | ISSN | Citations |
1 | 1549-7747 | 0 |
PageRank | References | Authors |
0.34 | 0 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Wei-Dong Dang | 1 | 13 | 3.24 |
| Mengyu Li | 2 | 0 | 0.34 |
| Dongmei Lv | 3 | 1 | 1.71 |
| Xinlin Sun | 4 | 1 | 1.07 |
| Zhongke Gao | 5 | 30 | 8.64 |