Recurrent and convolutional neural networks in classification of EEG signal for guided imagery and mental workload detection.

Postepski F, Wojcik GM, Wrobel K, Kawiak A, Zemla K, Sedek G

Open source

DOI
10.1038/s41598-025-92378-x
Published
2025 Mar 27
Container
Scientific reports
Publisher
Not recorded
Open access
yes

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BibTeX

@article{allodium:10.1038/s41598-025-92378-x,
  title = {Recurrent and convolutional neural networks in classification of EEG signal for guided imagery and mental workload detection.},
  author = {Postepski F and Wojcik GM and Wrobel K and Kawiak A and Zemla K and Sedek G},
  year = {2025},
  journal = {Scientific reports},
  doi = {10.1038/s41598-025-92378-x},
  url = {https://doi.org/10.1038/s41598-025-92378-x}
}

RIS

TY  - JOUR
TI  - Recurrent and convolutional neural networks in classification of EEG signal for guided imagery and mental workload detection.
AU  - Postepski F
AU  - Wojcik GM
AU  - Wrobel K
AU  - Kawiak A
AU  - Zemla K
AU  - Sedek G
PY  - 2025
JO  - Scientific reports
DO  - 10.1038/s41598-025-92378-x
UR  - https://doi.org/10.1038/s41598-025-92378-x
ER  -

APA

F, P., GM, W., K, W., A, K., K, Z., & G, S. (2025). Recurrent and convolutional neural networks in classification of EEG signal for guided imagery and mental workload detection.. Scientific reports. https://doi.org/10.1038/s41598-025-92378-x

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