Estimating workload using EEG spectral power and ERPs in the n-back task

By A. Brouwer, M. Hogervorst, Jan B. F. van Erp, T. Heffelaar, P. Zimmerman, Robert Oostenveld. Journal of Neural Engineering, 2012

414 citations recorded by the source corpus.

Subfields: Cardiology and Cardiovascular Medicine, Cognitive Neuroscience

View Paper: https://www.semanticscholar.org/paper/4051028f23282682c1826cf570ec67799b7a5706

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Cardiology and Cardiovascular Medicine

1. Changkun Ou
2. Sven Mayer
3. Francesco Chiossi

In Cognitive Neuroscience

1. Changkun Ou
2. Sven Mayer
3. Christian Herff
4. Francesco Chiossi

Citations in the corpus

• Mental workload during n-back task—quantified in the prefrontal cortex using fNIRS (2014, background): “We present the results for window length of 15 s as well, as this length has been used for workload evaluation with EEG before (Kothe and Makeig, 2011).”
• Exploring Physiological Correlates of Visual Complexity Adaptation: Insights from EDA, ECG, and EEG Data for Adaptation Evaluation in VR Adaptive Systems (2023, methodology): “Moreover, we computed the ratio of midline theta activity’s absolute power to posterior alpha activity’s absolute power as an implicit measure of workload [7, 27].”