Design a novel BCI for neurorehabilitation using concurrent LFP and EEG features: a case study
Brain-computer interfaces (BCI) that enables people with severe motor disabilities to use their brain signals for direct control of objects have attracted increased interest in rehabilitation. To date, no study has investigated feasibility of the BCI framework incorporating both intracortical and sc...
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sg-ntu-dr.10356-1637672022-12-16T03:12:39Z Design a novel BCI for neurorehabilitation using concurrent LFP and EEG features: a case study Feng, Zhao Sun, Yi Qian, Linze Qi, Yu Wang, Yueming Guan, Cuntai Sun, Yu School of Computer Science and Engineering Science::Medicine Brain Computer Interface Motor Imagery Brain-computer interfaces (BCI) that enables people with severe motor disabilities to use their brain signals for direct control of objects have attracted increased interest in rehabilitation. To date, no study has investigated feasibility of the BCI framework incorporating both intracortical and scalp signals. This work was supported in part by the National Natural Science Foundation of China under Grants 81801785 and 82172056, the grants from the Zhejiang Lab (2019KE0AD01), in part by the Fundamental Research Funds for the Central Universities (2020FZZX01-005), and in part by the National Key R&D Program of China (2018YFA0701400) and Zhejiang University Global Partnership Fund (100000-11320). 2022-12-16T03:12:39Z 2022-12-16T03:12:39Z 2021 Journal Article Feng, Z., Sun, Y., Qian, L., Qi, Y., Wang, Y., Guan, C. & Sun, Y. (2021). Design a novel BCI for neurorehabilitation using concurrent LFP and EEG features: a case study. IEEE Transactions On Biomedical Engineering, 69(5), 1554-1563. https://dx.doi.org/10.1109/TBME.2021.3115799 0018-9294 https://hdl.handle.net/10356/163767 10.1109/TBME.2021.3115799 34582344 2-s2.0-85128801020 5 69 1554 1563 en IEEE Transactions on Biomedical Engineering © 2021 IEEE. All rights reserved. |
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Science::Medicine Brain Computer Interface Motor Imagery |
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Science::Medicine Brain Computer Interface Motor Imagery Feng, Zhao Sun, Yi Qian, Linze Qi, Yu Wang, Yueming Guan, Cuntai Sun, Yu Design a novel BCI for neurorehabilitation using concurrent LFP and EEG features: a case study |
| description |
Brain-computer interfaces (BCI) that enables people with severe motor disabilities to use their brain signals for direct control of objects have attracted increased interest in rehabilitation. To date, no study has investigated feasibility of the BCI framework incorporating both intracortical and scalp signals. |
| author2 |
School of Computer Science and Engineering |
| author_facet |
School of Computer Science and Engineering Feng, Zhao Sun, Yi Qian, Linze Qi, Yu Wang, Yueming Guan, Cuntai Sun, Yu |
| format |
Article |
| author |
Feng, Zhao Sun, Yi Qian, Linze Qi, Yu Wang, Yueming Guan, Cuntai Sun, Yu |
| author_sort |
Feng, Zhao |
| title |
Design a novel BCI for neurorehabilitation using concurrent LFP and EEG features: a case study |
| title_short |
Design a novel BCI for neurorehabilitation using concurrent LFP and EEG features: a case study |
| title_full |
Design a novel BCI for neurorehabilitation using concurrent LFP and EEG features: a case study |
| title_fullStr |
Design a novel BCI for neurorehabilitation using concurrent LFP and EEG features: a case study |
| title_full_unstemmed |
Design a novel BCI for neurorehabilitation using concurrent LFP and EEG features: a case study |
| title_sort |
design a novel bci for neurorehabilitation using concurrent lfp and eeg features: a case study |
| publishDate |
2022 |
| url |
https://hdl.handle.net/10356/163767 |
| _version_ |
1753801162051551232 |