IEEE Systems, Man and Cybernetics Magazine - January 2022 - 4
Predicting
Cognitive Load of
an Individual With
Knowledge Gained
From Others
Improvements in Performance
Using Crowdsourcing
by Syed Moshfeq Salaken,
Imali Hettiarachchi, Afsana Ahmed Munia,
Md Mehedi Hasan, Abbas Khosravi,
Shady Mohamed, and Ashikur Rahman
U
4
nderstanding cognitive load is important due
to its inherent implications across many different
disciplines. This is, in general, a difficult
task due to personal nature of data
normally used to infer cognitive load. In
addition, an individual changes over time and his/her pattern
of data changes as well, which implies past data from
an individual may not reliably predict the future cognitive
load of the same individual. In this article, we show that
utilization of data from other people (a.k.a. crowdsourcing)
offers a significant improvement in classifier performance
when predicting cognitive load. We reveal that the
improvement is substantial compared to an individualistic
model and is statistically significant.
Background
Recently, there has been a significant amount of work
being done to predict cognitive load due to its necessity in
Digital Object Identifier 10.1109/MSMC.2021.3103498
Date of current version: 14 January 2022
IEEE SYSTEMS, MAN, & CYBERNETICS MAGAZINE January 2022
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IEEE Systems, Man and Cybernetics Magazine - January 2022
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