Developing intelligent systems to assess mental workload in office workers
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Eduarda Pereira [1] ; Ana Lima [1] ; Luís Sigcha [1] ; Diogo Sousa ; Ângelo Sousa ; Francisco Lopes ; Daniel Sá ; Leonila Fernandes ; Abdulay Abreu ; Paulo Cardoso ; Nélson Costa [1]
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[1] Universidade do Minho
Universidade do Minho
Braga (São José de São Lázaro), Portugal
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- Localización: ORPjournal, ISSN-e 2385-3832, Nº. Extra 1, 2023 (Ejemplar dedicado a: Proceedings XXIII International Congress on Occupational Risk Prevention), pág. 41
- Idioma: inglés
- Enlaces
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Resumen
The growing availability of technological tools is changing where and how we work. Therefore, the “new normal” of work increasingly includes dealing with a computer. Computer work includes different tasks such as programming, data entry, remote work, and office work. This kind of work can have high cognitive demands, so people must manage their mental workload to maintain their mental health and overall well-being. Mental workload can be influenced by several factors, the naturalness of performing a task, the complexity of the work, and the pace and intensity of the work environment. In this article, we explore the importance of developing intelligent monitoring systems to assess the mental workload of office workers. These systems turn essential to ensure that workers and organizations can manage this strain effectively, avoiding the negative consequences of high levels of mental workload, which directly impact the productivity of the worker, health, and wellbeing. To determine the level of mental workload, machine learning models can be employed.
