A survey on measuring cognitive workload in human-computer interaction

T Kosch, J Karolus, J Zagermann, H Reiterer… - ACM Computing …, 2023 - dl.acm.org
The ever-increasing number of computing devices around us results in more and more
systems competing for our attention, making cognitive workload a crucial factor for the user …

EEG-based brain-computer interfaces (BCIs): A survey of recent studies on signal sensing technologies and computational intelligence approaches and their …

X Gu, Z Cao, A Jolfaei, P Xu, D Wu… - … /ACM transactions on …, 2021 - ieeexplore.ieee.org
Brain-Computer interfaces (BCIs) enhance the capability of human brain activities to interact
with the environment. Recent advancements in technology and machine learning algorithms …

Mental workload during n-back task—quantified in the prefrontal cortex using fNIRS

C Herff, D Heger, O Fortmann, J Hennrich… - Frontiers in human …, 2014 - frontiersin.org
When interacting with technical systems, users experience mental workload. Particularly in
multitasking scenarios (eg, interacting with the car navigation system while driving) it is …

The effect of poor source code lexicon and readability on developers' cognitive load

S Fakhoury, Y Ma, V Arnaoudova… - Proceedings of the 26th …, 2018 - dl.acm.org
It has been well documented that a large portion of the cost of any software lies in the time
spent by developers in understanding a program's source code before any changes can be …

Real-time state estimation in a flight simulator using fNIRS

T Gateau, G Durantin, F Lancelot, S Scannella… - PloS one, 2015 - journals.plos.org
Working memory is a key executive function for flying an aircraft. This function is particularly
critical when pilots have to recall series of air traffic control instructions. However, working …

Dynamic difficulty using brain metrics of workload

D Afergan, EM Peck, ET Solovey, A Jenkins… - Proceedings of the …, 2014 - dl.acm.org
Dynamic difficulty adjustments can be used in human-computer systems in order to improve
user engagement and performance. In this paper, we use functional near-infrared …

[HTML][HTML] Physiological indicators of task demand, fatigue, and cognition in future digital manufacturing environments

EM Argyle, A Marinescu, ML Wilson, G Lawson… - International Journal of …, 2021 - Elsevier
Abstract As Digital Manufacturing transforms traditionally physical work into more system-
monitoring tasks, new methods are required for understanding people's mental workload …

Electroencephalogram and physiological signal analysis for assessing flow in games

R Berta, F Bellotti, A De Gloria… - … Intelligence and AI …, 2013 - ieeexplore.ieee.org
Passive brain-computer interaction (BCI) can provide useful information to understand a
user's state and anticipate intentions, which is needed to support adaptivity and …

Toward workload-based adaptive automation: The utility of fNIRS for measuring load in multiple resources in the brain

LM Hirshfield, C Wickens, E Doherty… - … Journal of Human …, 2024 - Taylor & Francis
We investigate the utility of functional near-infrared spectroscopy (fNIRS) for workload-based
adaptive automation through the lens of multiple resource theory. We focus on the criteria of …

Using fNIRS brain sensing to evaluate information visualization interfaces

EMM Peck, BF Yuksel, A Ottley, RJK Jacob… - Proceedings of the …, 2013 - dl.acm.org
We show how brain sensing can lend insight to the evaluation of visual interfaces and
establish a role for fNIRS in visualization. Research suggests that the evaluation of visual …