A Brain-Computer Interface Application Based on P300 Evoked EEG Potentials for Enabling the Communication Between Users and Chat GPT
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Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-56075-0_22
Reference13 articles.
1. Kurczak, J., Białas, K., Chalupnik, R., Kedziora, M.: Using Brain-Computer Interface (BCI) and artificial intelligence for EEG signal analysis. In: Szczerbicki, E., Wojtkiewicz, K., Van Nguyen, S., Pietranik, M., Krótkiewicz, M. (eds.) Recent Challenges in Intelligent Information and Database Systems: 14th Asian Conference, ACIIDS 2022, Ho Chi Minh City, Vietnam, November 28-30, 2022, Proceedings, pp. 214–226. Springer Nature Singapore, Singapore (2022). https://doi.org/10.1007/978-981-19-8234-7_17
2. Farwell, L.A., Donchin, E.: Talking off the top of your head: toward a mental prosthesis utilizing event-related brain potentials. Electroencephalogr. Clin. Neurophysiol. 70, 510 (1988)
3. Cao, Z.: A review of artificial intelligence for EEG-based brain−computer interfaces and applications. Brain Sci. Adv. 6(3), 162–170 (2020). https://doi.org/10.26599/BSA.2020.9050017
4. Tang, J., LeBel, A., Jain, S., et al.: Semantic reconstruction of continuous language from non-invasive brain recordings. Nat. Neurosci. 26, 858–866 (2023). https://doi.org/10.1038/s41593-023-01304-9
5. O'Leary, K.: MRI decoders translate thoughts into words. Nature medicine, Advance online publication (2023). https://doi.org/10.1038/d41591-023-00044-4
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