Classification Algorithms in Adaptive Systems for Neuro-Ergonomic Applications
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Publisher
Springer International Publishing
Link
http://link.springer.com/content/pdf/10.1007/978-3-319-94223-0_39
Reference22 articles.
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2. Hannula, M., Huttunen, K., Koskelo, J., Laitinen, T., Leino, T.: Comparison between artificial neural network and multilinear regression models in an evaluation of cognitive workload in a flight simulator. Comput. Biol. Med. 38, 1163–1170 (2008). https://doi.org/10.1016/j.compbiomed.2008.09.007
3. Prinzel III, L.J., Freeman, F.G., Scerbo, M.W., Mikulka, P.J., Pope, A.T.: Effects of a psychophysiological system for adaptive automation on performance, workload, and the event-related potential P300 component. Hum. Factors 45, 601–614 (2003)
4. Prinzel, L.J., Freeman, F.G., Scerbo, M.W., Mikulka, P.J., Pope, A.T.: A closed-loop system for examining psychophysiological measures for adaptive task allocation. Int. J. Aviat. Psychol. 10, 393–410 (2000). https://doi.org/10.1207/S15327108IJAP1004_6
5. Freeman, F.G., Mikulka, P.J., Scerbo, M.W., Prinzel, L.J., Clouatre, K.: Evaluation of a psychophysiologically controlled adaptive automation system, using performance on a tracking task. Appl. Psychophysiol. Biofeedback 25, 103–115 (2000)
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