Abstract
The brain mechanism of selective attention plays a key role in determining the success of a human’s interaction with a device. If the user has to perform concurrent tasks by interacting simultaneously with more than one device, her/his attention is directed at one of the devices at a time. Attention can therefore be seen as a shared resource, and the attentional mechanisms play the role of a task scheduler. In this paper we propose an algorithm for simulating the human selective attention. Simulations can then be used to study situations in which a user has to interact simultaneously with multiple devices. This kind of study is particularly important in safety-critical contexts in which failures in the main task, such as driving a car or setting an infusion pump, may have serious consequences.
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Acknowledgements
This work has been supported by the project “Metodologie informatiche avanzate per l’analisi di dati biomedici (Advanced computational methodologies for the analysis of biomedical data)” funded by the University of Pisa (PRA_2017_44).
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Broccia, G., Milazzo, P., Ölveczky, P.C. (2018). An Algorithm for Simulating Human Selective Attention. In: Cerone, A., Roveri, M. (eds) Software Engineering and Formal Methods. SEFM 2017. Lecture Notes in Computer Science(), vol 10729. Springer, Cham. https://doi.org/10.1007/978-3-319-74781-1_4
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DOI: https://doi.org/10.1007/978-3-319-74781-1_4
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