Physiological model to classify physical and cognitive workload during gaming activities

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Abstract

Some of new approaches in Human Factors and Ergonomics are based on the assessment of cognitive and physical workload using physiological measurements. Nevertheless, the relationship between both requires to get in depth about its causes and effects. The main goal of this work was to develop a model to distinguish the impact of physical and cognitive workload, leaning on physiological response analysis. To do this, senior citizens performed a set of tasks of video games, where the predominance of each type of workload is known. Facial electromyography, galvanic skin response and electrocardiogram signals from subjects were recorded while they performed the tasks. The parameters extracted were used to design a classification model to predict the type of workload involved in a task. The designed model is based in a reduced number of variables and it achieves a 75.6% of success to differentiate physical and cognitive demands.

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Arroyo-Gómez, N., Laparra-Hernández, J., Soler-Valero, A., Medina, E., & de Rosario, H. (2018). Physiological model to classify physical and cognitive workload during gaming activities. In Advances in Intelligent Systems and Computing (Vol. 586, pp. 246–254). Springer Verlag. https://doi.org/10.1007/978-3-319-60642-2_23

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