20.500.12556/DiRROS-22927 A review of methods for unobtrusive measurement of work-related well-being 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. affective computing ambient intelligence work-related well-being behavioral markers delovno okolje obrazi izrazi meritve dobro počutje true false true MDPI Švica Angleški jezik Slovenski jezik © 2025 by the authors. Neznano 2025-07-08 13:37:23 2025-07-08 13:37:23 2025-10-24 03:52:45 0000-00-00 00:00:00 2025 0 0 Nasl. z nasl. zaslona; Opis vira z dne 8. 7. 2025; str. 1-22 iss. 3 Vol. 7 2025 0000-00-00 Zaloznikova Objavljeno NiDoloceno 2025-05-28 2025-06-28 2025-07-01 004.93+61 2504-4990 10.3390/make7030062 241787651 https://www.mdpi.com/2504-4990/7/3/62 1 ebffe512-5bef-11f0-8080-001a4af901a5 https://dirros.openscience.si/Dokument.php?lang=slv&id=33405 RAZ_Anzur_Zoja_2025.pdf RAZ_Anzur_Zoja_2025.pdf 1 0B65AE7AD2649C5B52AF25E2D0F573C4 c2ac12ab1149866bc35298ee62cee415632719af8665a09121e5644471f14c08 b717a470-5bf0-11f0-8080-001a4af901a5 https://dirros.openscience.si/Dokument.php?lang=slv&id=33406 Institut Jožef Stefan 0 0 0