Copyright: © 2026 by the authors. Licensee: Pirogov University.
This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution license (CC BY).

ORIGINAL RESEARCH

Testing a speech rehabilitation brain-computer interface for use in clinical settings

Protopova МA1 , Gorshkov GI1 , Schalk G2 , Dragoy ОV1
About authors

1 HSE University, Moscow, Russia

2 Fudan University, Shanghai, China

ur.liamg@airamavopotorp

About paper

The study was carried out within the framework of the HSE Fundamental Research Program

The authors declare no obvious or potential conflicts of interest related to the publication of this article. The study was approved by the HSE University Committee for Internal Surveys and Ethical Review of Empirical Research Projects. Participants signed informed consent forms.

Received: 2024-09-30 Accepted: 2025-12-22 Published online: 2026-02-10
|
  1. Chu, C. J. (2014). High density EEG—What do we have to lose? Clinical Neurophysiology, 126(3), 433. https://doi.org/10.1016/j.clinph.2014.07.003
  2. Ehrhardt, N. M., Niehoff, C., Oßwald, A. C., Antonenko, D., Lucchese, G., & Fleischmann, R. (2024). Comparison of dry and wet electroencephalography for the assessment of cognitive evoked potentials and sensor-level connectivity. Frontiers in Neuroscience, 18, 1441799. https://doi.org/10.3389/fnins.2024.1441799
  3. Hinrichs, H., Scholz, M., Baum, A. K., Kam, J. W., Knight, R. T., & Heinze, H. J. (2020). Comparison between a wireless dry electrode EEG system with a conventional wired wet electrode EEG system for clinical applications. Scientific Reports, 10(1), 5218. https://doi.org/10.1038/s41598-020-62154-0
  4. Huang, G., Zhao, Z., Zhang, S., Hu, Z., Fan, J., Fu, M., ... & Dan, G. (2023). Discrepancy between inter-and intra-subject variability in EEG-based motor imagery brain-computer interface: Evidence from multiple perspectives. Frontiers in Neuroscience, 17, 1122661. https://doi.org/10.3389/fnins.2023.1122661
  5. Kam, J. W., Griffin, S., Shen, A., Patel, S., Hinrichs, H., Heinze, H. J., ... & Knight, R. T. (2019). Systematic comparison between a wireless EEG system with dry electrodes and a wired EEG system with wet electrodes. NeuroImage, 184, 119–129. https://doi.org/10.1016/j.neuroimage.2018.09.012
  6. Lopez-Gordo, M. A., Sanchez-Morillo, D., & Valle, F. P. (2014). Dry EEG electrodes. Sensors, 14(7), 12847–12870. https://doi.org/10.3390/s140712847
  7. Musso, M., Hübner, D., Schwarzkopf, S., Bernodusson, M., LeVan, P., Weiller, C., & Tangermann, M. (2022). Aphasia recovery by language training using a brain–computer interface: A proof-of-concept study. Brain Communications, 4(1), fcac008. https://doi.org/10.1093/braincomms/fcac008
  8. Niu, X., Gao, X., Liu, Y., & Liu, H. (2021). Surface bioelectric dry electrodes: A review. Measurement, 183, 109774. https://doi.org/10.1016/j.measurement.2021.109774
  9. Noble, S. C., Ward, T., & Ringwood, J. V. (2024, July). Assessing the impact of environment and electrode configuration on P300 speller performance and EEG signal quality. 2024 46th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 1–4. IEEE. https://doi.org/10.1109/EMBC53108.2024.10782158
  10. Rusanu, O. A. (2024, March). A brain-computer interface for controlling a wheelchair based virtual simulation using the Unicorn EEG headset and the P300 speller board. In International Conference on Smart Technologies & Education (pp. 423–435). Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-61905-2_41
  11. Saha, S., & Baumert, M. (2020). Intra-and inter-subject variability in EEG-based sensorimotor brain computer interface: A review. Frontiers in Computational Neuroscience, 13, 87. https://doi.org/10.3389/fncom.2019.00087
  12. Schalk, G., McFarland, D. J., Hinterberger, T., Birbaumer, N., & Wolpaw, J. R. (2004). BCI2000: A general-purpose brain-computer interface (BCI) system. IEEE Transactions on Biomedical Engineering, 51(6), 1034–1043. https://doi.org/10.1109/TBME.2004.827072
  13. Teplan, M. (2002). Fundamentals of EEG measurement. Measurement Science Review, 2(2), 1–11.
  14. Wolpaw, J. R., & Wolpaw, E. W. (2012). Brain-computer interfaces: Something new under the sun. Brain-Computer Interfaces: Principles and Practice, 14.
  15. Zhuang, M., Wu, Q., Wan, F., & Hu, Y. (2020). State-of-the-art non-invasive brain–computer interface for neural rehabilitation: A review. Journal of Neurorestoratology, 8(1), 12–25. https://doi.org/10.26599/JNR.2020.9040001