Contactless Physiological Assessment of Mental Workload During Teleworking-like Task
Human physiological parameters have been proven as reliable and objective indicators of user’s mental states, such as the Mental Workload. However, standard methodologies for evaluating physiological parameters generally imply a certain grade of invasiven
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University of Rome, Rome, Italy [email protected] 2 BrainSigns srl, Rome, Italy 3 Department of Business and Management, LUISS University, Rome, Italy 4 Department of Molecular Medicine, Sapienza University of Rome, Rome, Italy 5 IRCCS Fondazione Santa Lucia, Rome, Italy 6 Department of Computer Science, Hangzhou Dianzi University, Hangzhou, China
Abstract. Human physiological parameters have been proven as reliable and objective indicators of user’s mental states, such as the Mental Workload. However, standard methodologies for evaluating physiological parameters generally imply a certain grade of invasiveness. It is largely demonstrated the relevance of monitoring workers to improve their working conditions. A contactless approach to estimate workers’ physiological parameters would be highly suitable because it would not interfere with the working activities and comfort of the workers. Additionally, it would be very appropriate for teleworking settings. In this paper, participants’ facial videos were recorded while dealing with arithmetic tasks with the aims to 1) evaluate the possibility to estimate their Heart Rate (HR) through facial video analysis, and 2) assess their mental workload under the different experimental conditions. The HR was also estimated through last-generation smartwatches. The results demonstrated that there was no difference between the HR estimated via the contactless technique and smartwatches, and how it was possible to discriminate the two mental workload levels by employing the proposed methodology. Keywords: Contactless · Physiological signals · Autonomic parameters · Teleworking · Mental workload · Heart rate
1 Introduction According to the Eurofund report, in 2018 approximately 3.2 million non-fatal and 3.793 fatal work-related accidents occurred in Europe [1], and the 7.4% of the EU population suffered from one or more work-related health problems [1]. Among the principal causes of work-related accidents there is the Human Factor (HF) [2, 3]. In fact, it has been demonstrated that human errors are the main causes of work-related accidents [4–6]. Workers’ common errors are largely correlated with the condition of © Springer Nature Switzerland AG 2020 L. Longo and M. C. Leva (Eds.): H-WORKLOAD 2020, CCIS 1318, pp. 76–86, 2020. https://doi.org/10.1007/978-3-030-62302-9_5
Contactless Physiological Assessment of Mental Workload
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high mental workload, tiredness and distractions [7, 8]. These findings clearly indicate the relevance of being able to monitor in real time worker’s psychophysical state, such as mental workload and tiredness, in working operational environments [9]. In this context, scientific literature largely highlighted the limit of using subjective methodologies to evaluate such HFs [10–12]. As a potential countermeasure, in the last decades neuroscientific disciplines have been dedicating a great effort in investigating human physiological correlates of user’s mental states in order to develop monitoring tools able to detect incoming cognitive impairments
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