Towards using the Yerkes-Dodson Law to select optimal training difficulty in firefighter simulations: A machine learning based ECG approach
| Zugehörige Institution(en) am KIT | Institut für Technik der Informationsverarbeitung (ITIV) |
| Publikationstyp | Proceedingsbeitrag |
| Publikationsjahr | 2025 |
| Sprache | Englisch |
| Identifikator | ISBN: 978-1-990800-61-0 ISSN: 2369-811X KITopen-ID: 1000188145 |
| Erschienen in | Proceedings of the 11th World Congress on Electrical Engineering and Computer Systems and Sciences (EECSS'25), Paris, France – August, 2025 |
| Veranstaltung | 11th World Congress on Electrical Engineering and Computer Systems and Sciences (EECSS 2025), Paris, Frankreich, 17.08.2025 – 19.08.2025 |
| Verlag | Avestia Publishing |
| Seiten | ICBES 199 |
| Serie | World Congress on Electrical Engineering and Computer Systems and Science |
| Nachgewiesen in | Scopus OpenAlex |