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A Review of Methods for Unobtrusive Measurement of Work-Related Well-Being
Auteur(s)
Zoja Anžur
Klara Žinkovič
Junoš Lukan
Pietro Barbiero
Gašper Slapničar
Mohan Li
Martin Gjoreski
Sebastijan Trojer
Mitja Luštrek
Marc Langheinrich
Date de parution
2025
In
Machine Learning and Knowledge Extraction
Vol.
7
De la page
1
A la page
22
Résumé
Work-related well-being is an important research topic, as it is linked to various aspects of individuals’ lives, including job performance. To measure it effectively, unobtrusive sensors are desirable to minimize the burden on employees. Because there is a lack of consensus on the definitions of well-being in the psychological literature in terms of its dimensions, our work begins by proposing a conceptualization of well-being based on the refined definition of health provided by the World Health Organization. We focus on reviewing the existing literature on the unobtrusive measurement of well-being. In our literature review, we focus on affect, engagement, fatigue, stress, sleep deprivation, physical comfort, and social interactions. Our initial search resulted in a total of 644 studies, from which we then reviewed 35, revealing a variety of behavioral markers such as facial expressions, posture, eye movements, and speech. The most commonly used sensory devices were red, green, and blue (RGB) cameras, followed by microphones and smartphones. The methods capture a variety of behavioral markers, the most common being body movement, facial expressions, and posture. Our work serves as an investigation into various unobtrusive measuring methods applicable to the workplace context, aiming to foster a more employee-centric approach to the measurement of well-being and to emphasize its affective component.</jats:p>
Identifiants
Type de publication
journal article
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