Exploring cognitive load through neuropsychological features: an analysis using fNIRS-eye tracking
Author:
Funder
the Research and Innovation Plan Project of Shanghai Education Commission
Publisher
Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1007/s11517-024-03178-w.pdf
Reference58 articles.
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3. Paas F, Tuovinen JE, Tabbers H, Van Gerven PWM (2003) Cognitive load measurement as a means to advance cognitive load theory. Educ Psychol 38:63–71. https://doi.org/10.1207/s15326985ep3801_8
4. Liu Y, Ayaz H, Shewokis PA (2017) Mental workload classification with concurrent electroencephalography and functional near-infrared spectroscopy. Brain-Comput Inter 4:175–185. https://doi.org/10.1080/2326263X.2017.1304020
5. Cegovnik T, Stojmenova K, Jakus G, Sodnik J (2018) An analysis of the suitability of a low-cost eye tracker for assessing the cognitive load of drivers. Appl Ergon 68:1–11. https://doi.org/10.1016/j.apergo.2017.10.011
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