Analysis of Alternatives for Neural Network Training Techniques in Assessing Cognitive Workload

Author:

Elkin Colin,Devabhaktuni Vijay

Publisher

Springer International Publishing

Reference25 articles.

1. Elkin, C., Nittala, S., Devabhaktuni, V.: Fundamental cognitive workload assessment: a machine learning comparative approach. In: 8th International Conference on Applied Human Factors and Ergonomics (AHFE), pp. 275–284. Springer, Cham (2017)

2. Berka, C., et al.: EEG correlates of task engagement and mental workload in vigilance, learning, and memory tasks. Aviat. Space Environ. Med. 78(5), B231–B234 (2007)

3. Durantin, G., Gagnon, J.-F., Tremblay, S., Dehais, F.: Using near infrared spectroscopy and heart rate variability to detect mental overload. Behav. Brian Search 259, 16–23 (2014)

4. Niaz, M., Logie, R.H.: Working memory, mental capacity and science education: towards an understanding of the ‘working memory overload hypothesis’. Oxford Rev. Educ. 19(4), 511–525 (1993)

5. Wilson, G.F., Russell, C.A.: Real-time assessment of mental workload using psychophysiological measures and artificial neural networks. Hum. Factors 45(4), 635–644 (2016)

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