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Title:A review of methods for unobtrusive measurement of work-related well-being
Authors:ID Anžur, Zoja, Institut "Jožef Stefan" (Author)
ID Žinkovič, Klara, Institut "Jožef Stefan" (Author)
ID Lukan, Junoš, Institut "Jožef Stefan" (Author)
ID Slapničar, Gašper, Institut "Jožef Stefan" (Author)
ID Trojer, Sebastijan, Institut "Jožef Stefan" (Author)
ID Luštrek, Mitja, Institut "Jožef Stefan" (Author)
ID Langheinrich, Marc (Author), et al.
Files:URL URL - Source URL, visit https://www.mdpi.com/2504-4990/7/3/62
 
.pdf PDF - Presentation file, download (565,62 KB)
MD5: 0B65AE7AD2649C5B52AF25E2D0F573C4
 
Language:English
Typology:1.02 - Review Article
Organization:Logo IJS - Jožef Stefan Institute
Abstract: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.
Keywords:affective computing, ambient intelligence, work-related well-being, behavioral markers
Publication status:Published
Publication version:Version of Record
Submitted for review:28.05.2025
Article acceptance date:28.06.2025
Publication date:01.07.2025
Publisher:MDPI
Year of publishing:2025
Number of pages:str. 1-22
Numbering:Vol. 7, iss. 3
Source:Švica
PID:20.500.12556/DiRROS-22927 New window
UDC:004.93+61
ISSN on article:2504-4990
DOI:10.3390/make7030062 New window
COBISS.SI-ID:241787651 New window
Copyright:© 2025 by the authors.
Note:Nasl. z nasl. zaslona; Opis vira z dne 8. 7. 2025;
Publication date in DiRROS:08.07.2025
Views:395
Downloads:240
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Record is a part of a journal

Title:Machine learning and knowledge extraction
Publisher:MDPI
ISSN:2504-4990
COBISS.SI-ID:1537706179 New window

Document is financed by a project

Funder:ARIS - Slovenian Research and Innovation Agency
Project number:N1-0319
Name:ZAUPAJ-MI: ZAUPAnja vredno izbolJšanje zadovoljstva in produktivnosti na delovnem mestu s pomočjo MIkro-zaznavanja v delovnem okolju

Funder:SNSF - Swiss National Science Foundation
Funding programme:Careers
Project number:216405
Name:XAI-PAC: Towards Explainable and Private Affective Computing

Licences

License:CC BY 4.0, Creative Commons Attribution 4.0 International
Link:http://creativecommons.org/licenses/by/4.0/
Description:This is the standard Creative Commons license that gives others maximum freedom to do what they want with the work as long as they credit the author.
Licensing start date:01.07.2025
Applies to:VoR

Secondary language

Language:Slovenian
Keywords:delovno okolje, obrazi, izrazi, meritve, dobro počutje


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