Contactless physiological assessment of mental workload during teleworking-like task
| Autor: | Gianluca Borghini, Gianluca Di Flumeri, Pietro Aricò, Alessia Vozzi, Nicolina Sciaraffa, Fabio Babiloni, Antonello Di Florio, Vincenzo Ronca, Dario Rossi |
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| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: |
contactless
business.industry Computer science autonomic parameters heart rate mental workload physiological signals teleworking 05 social sciences Workload Machine learning computer.software_genre Task (project management) Smartwatch 03 medical and health sciences 0302 clinical medicine 0501 psychology and cognitive sciences Relevance (information retrieval) Artificial intelligence business computer 050107 human factors 030217 neurology & neurosurgery |
| Zdroj: | Communications in Computer and Information Science Communications in Computer and Information Science-Human Mental Workload: Models and Applications Communications in Computer and Information Science ISBN: 9783030623012 H-WORKLOAD |
| ISSN: | 1865-0929 1865-0937 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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