The Potential of Cognitive Circles to Measure Mental Load

Human Pose & Activity RecognitionCognitive Impairment & Neurodiversity (Autism, ADHD, Dyslexia)Computational Methods in HCIUniversity Professors & ResearchersHCI ResearchersCognitive Scientists

In Human-Computer Interaction, Usability, and Interaction Design, obtaining objective measures of mental workload is desirable yet challenging, as current methods are either costly and intrusive or subjective and unreliable. To overcome these limitations, we devised Cognitive Circles, a technique that estimates workload by analyzing the kinematic properties of circular traces drawn on a tablet as people simultaneously perform cognitively demanding tasks of different types (arithmetic, reading, and spatial reasoning). We investigate the feasibility of this approach and lay the foundations for establishing its viability through a controlled experiment that addresses two questions: (A) Do participants' traces reliably encode information to predict the tasks' difficulty? and (B) Do predictive patterns generalize across tasks in different cognitive activities? Our results show that Cognitive Circles can predict task difficulty with an average accuracy of 75% (reaching up to 94% for spatial reasoning tasks), capturing meaningful signatures of mental workload (A). Prediction performance, however, varies substantially across task types (B), suggesting that each task domain induces people to exhibit distinct kinematic patterns. These findings highlight Cognitive Circles as a promising low-cost approach to workload assessment and point to its potential for informing adaptive HCI and the design of cognitively aware systems.

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https://hci.top/en/papers/uist/206908/2025

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DOI: https://doi.org/10.1145/3746059.3747716
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UIST
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2025
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4 authors
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Human Pose & Activity Recognition, Cognitive Impairment & Neurodiversity (Autism, ADHD, Dyslexia), Computational Methods in HCI
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University Professors & Researchers, HCI Researchers, Cognitive Scientists
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