| Autor: |
Zhongpeng Wang, Lu Yang, Mengya Wang, Yijie Zhou, Long Chen, Bin Gu, Shuang Liu, Minpeng Xu, Feng He, Dong Ming |
| Jazyk: |
angličtina |
| Rok vydání: |
2023 |
| Předmět: |
|
| Zdroj: |
IEEE Transactions on Neural Systems and Rehabilitation Engineering, Vol 31, Pp 2457-2467 (2023) |
| Druh dokumentu: |
article |
| ISSN: |
1558-0210 |
| DOI: |
10.1109/TNSRE.2023.3275572 |
| Popis: |
Brain-computer interface (BCI)-based motor rehabilitation feedback training system can facilitate motor function reconstruction, but its rehabilitation mechanism with suitable training protocol is unclear, which affects the application effect. To this end, we probed the electroencephalographic (EEG) activations induced by motor imagery (MI) and action observation (AO) to provide an effective method to optimize motor feedback training. We grouped subjects according to their alpha–band sensorimotor cortical excitability under MI and AO conditions, and investigated the EEG response under the same paradigm between groups and different motor paradigms within group, respectively. The results showed that there were significant differences in sensorimotor activations between two groups of subjects. Specifically, the group with weaker MI induced EEG features, could achieve stronger sensorimotor activations in AO than that of other conditions. The group with stronger MI induced EEG features, could achieve stronger sensorimotor activations in the MI+AO than that of other conditions. We also explored their classification and brain network differences, which might try to explain the EEG mechanism in different individuals and help stroke patients to choose appropriate subject-specific motor training paradigm for their rehabilitation and better treatment outcomes. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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