Open Access
| Issue |
BIO Web Conf.
Volume 174, 2025
2025 7th International Conference on Biotechnology and Biomedicine (ICBB 2025)
|
|
|---|---|---|
| Article Number | 02012 | |
| Number of page(s) | 5 | |
| Section | Innovations in Therapeutics and Disease Mechanisms | |
| DOI | https://doi.org/10.1051/bioconf/202517402012 | |
| Published online | 12 May 2025 | |
- K. Martín-Chinea, J. F. Gómez-González， L. Acosta, “A New PLV-Spatial Filtering to Improve the Classification Performance in BCI Systems,” in IEEE Transactions on Neural Systems and Rehabilitation Engineering, vol. 30, pp. 2275-2282, 2022. [CrossRef] [PubMed] [Google Scholar]
- M. A. García-Vellisca, A. Matran-Fernandez, R. Poli and L. Citi, “Hand-movement Prediction from EMG with LSTM-Recurrent Neural Networks,” 2021 Global Medical Engineering Physics Exchanges/Pan American Health Care Exchanges (GMEPE/PAHCE), Sevilla, Spain, 2021, pp. 1-5. [Google Scholar]
- J. R. Wolpaw, D. J. McFarland, T. M. Vaughan and G. Schalk, “The Wadsworth Center brain-computer interface (BCI) research and development program,” in IEEE Transactions on Neural Systems and Rehabilitation Engineering, vol. 11, no. 2, pp. 1-4, June 2003. [CrossRef] [PubMed] [Google Scholar]
- Huang Wenqi. Motion image classification based on deep learning and whole brain EEG multi-domain features [D]. Lanzhou Jiaotong University,2022. [Google Scholar]
- Z. Feng et al., “Design a Novel BCI for Neurorehabilitation Using Concurrent LFP and EEG Features: A Case Study,” in IEEE Transactions on Biomedical Engineering, vol. 69, no. 5, pp. 1554-1563, May 2022. [CrossRef] [PubMed] [Google Scholar]
- Liu Enjie. Design of Flexible strain Sensor based on PDMS and its Application in manipulator [D]. Hebei: Hebei University,2022. [Google Scholar]
- Kong, X. Gu and B. Yan, “Development of a drug addiction rehabilitation training system based on BCI-VR technology,” 2019 Intelligent Rehabilitation and Human-machine Engineering Conference (IRHE-2019), Qinhuangdao, China, 2019, pp. 1-5. [Google Scholar]
- B. Borgheai et al., “Enhancing Communication for People in Late-Stage ALS Using an fNIRS-Based BCI System,” in IEEE Transactions on Neural Systems and Rehabilitation Engineering, vol. 28, no. 5, pp. 1198-1207, May 2020. [CrossRef] [PubMed] [Google Scholar]
- Tang et al., “An Upper-Limb Rehabilitation Exoskeleton System Controlled by MI Recognition Model with Deep Emphasized Informative Features in a VR Scene,” in IEEE Transactions on Neural Systems and Rehabilitation Engineering, vol. 31, pp. 4390-4401, 2023. [CrossRef] [PubMed] [Google Scholar]
- -H. Su, C. -H. Chen, C. -H. Chen, Y. -L. Zhang and L.-W. Ko, “An Exoskeleton BCI System for Stroke Rehabilitation Using Multi-modality Training Mode,” 2023 International Automatic Control Conference, Penghu, Taiwan, 2023, pp. 1-6. [Google Scholar]
- Trocellier, B. N’Kaoua and F. Lotte, “Identifying factors influencing the outcome of BCI-based post stroke motor rehabilitation towards its personalization with Artificial Intelligence,” 2022 IEEE International Conference on Metrology for Extended Reality, Artificial Intelligence and Neural Engineering (MetroXRAINE), Rome, Italy, 2022, pp. 151-156. [Google Scholar]
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