Assessing Cognitive Load via Pupillometry

A fierce search is called for a reliable, non-intrusive, and real-time capable method for assessing a person’s experienced cognitive load. Software systems capable of adapting their complexity to the mental demand of their users would be beneficial in a variety of domains. The only disclosed algorit...

Full description

Saved in:
Bibliographic Details
Published inAdvances in Artificial Intelligence and Applied Cognitive Computing pp. 1087 - 1096
Main Authors Weber, Pavel, Rupprecht, Franca, Wiesen, Stefan, Hamann, Bernd, Ebert, Achim
Format Book Chapter
LanguageEnglish
Published Cham Springer International Publishing 2021
SeriesTransactions on Computational Science and Computational Intelligence
Subjects
Online AccessGet full text
ISBN9783030702953
3030702952
ISSN2569-7072
2569-7080
DOI10.1007/978-3-030-70296-0_86

Cover

More Information
Summary:A fierce search is called for a reliable, non-intrusive, and real-time capable method for assessing a person’s experienced cognitive load. Software systems capable of adapting their complexity to the mental demand of their users would be beneficial in a variety of domains. The only disclosed algorithm that seems to reliably detect cognitive load in pupillometry signals—the index of pupillary activity (IPA)—has not yet been sufficiently validated. We take a first step in validating the IPA by applying it to a working memory experiment with finely granulated levels of difficulty, and comparing the results to traditional pupillometry metrics analyzed in cognitive research. Our findings confirm the significant positive correlation between task difficulty and IPA the authors stated.
ISBN:9783030702953
3030702952
ISSN:2569-7072
2569-7080
DOI:10.1007/978-3-030-70296-0_86