A Review of Methods for Unobtrusive Measurement of Work-Related Well-Being
Abstract
1. Introduction
2. Conceptualizing Well-Being
2.1. Taxonomies of Well-Being
2.2. Proposed Concept of Well-Being
- Psychological well-being: As per Ryff [19], psychological well-being includes happiness (the experience of pleasure) and eudaimonic well-being (referring to flourishing, engagement, feeling a sense of purpose):
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- Affect: Affect is defined as the experiences of negative and positive affect. As per the circumplex model [20], each affect can be described as a combination of two independent dimensions: pleasure and arousal. Negative affect is a negative well-being indicator, whereas positive affect is a positive well-being indicator.
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- Engagement: Engagement is defined as a state where an employee has a high level of energy, is enthusiastic, and is immersed in their work. Engagement is composed of vigor, dedication, and absorption. Vigor refers to high energy and resilience levels, dedication refers to being strongly involved in one’s work, and absorption refers to being focused on and immersed in one’s work [21]. Engagement is a positive well-being indicator.
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- Fatigue: Fatigue is defined as a state that happens as a consequence of long periods of demanding cognitive activity [20]. Fatigue is a negative well-being indicator.
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- Stress: As per the APA dictionary [22], stress is recognized as the physiological or psychological response to stressors, which can be either internal or external. The physiological response can manifest in sweating, a dry mouth, accelerated speech, etc., and influences how people behave and feel. Stress is a negative well-being indicator.
- Physical well-being: As per Seligman [23], physical well-being extends beyond the absence of sickness, capturing an individual’s capability to realize their fullest wellness potential:
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- Physical comfort: As defined by Kölsch et al. [24], the physical comfort zone is composed of postures and motions that are voluntarily adopted, as opposed to those that are avoided. Physical comfort positively impacts well-being.
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- Sleep deprivation: Sleep deprivation occurs when there is either a total absence of sleep or a reduction in sleep duration [25]. Sleep deprivation negatively impacts well-being.
- Social well-being: As per Pressman [26], social well-being is experienced when various social needs, such as the feeling of support and belonging, are met:
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- Social interactions: A social interaction is defined as a process that entails mutual interaction or responses between two or more individuals [27]. There is evidence of the link between frequent and deeper social interactions and well-being [28], indicating that enriching interactions and social support can contribute to increased well-being.
3. Paper Selection Method
- Focus on one of the identified sub-dimensions of well-being.
- Focus on unobtrusive sensing methods.
4. Psychological Well-Being
4.1. Affect
4.2. Engagement
4.3. Fatigue
4.4. Stress
5. Physical Well-Being
5.1. Physical Comfort
5.2. Sleep Deprivation
6. Social Well-Being
Social Interactions
7. Privacy-Aware Sensing
8. Proposed Setup
9. Discussion
10. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Data Availability Statement
Conflicts of Interest
Abbreviations
APA | American Psychological Association |
ML | machine learning |
PERCLOS | percentage of eyelid closure |
RGB | red, green, and blue |
WHO | World Health Organisation |
Appendix A
Sub-Dimension | Keywords Used |
---|---|
Physical comfort | (“comfort” OR “physical comfort”) AND ((“unobtrusive” OR “non-contact” OR “contact-free” OR “contact free”) AND (“sensors” OR “sensing”)) |
Sleep deprivation | (“sleepiness” OR “sleep deprivation”) AND ((“unobtrusive” OR “non-contact” OR “contact-free” OR “contact free”) AND (“sensors” OR “sensing”)) |
Engagement | (“engagement”) AND ((“unobtrusive” OR “non-contact” OR “contact-free” OR “contact free”) AND (“sensors” OR “sensing”)) |
Affect | (“emotions” OR “emotion” OR “affect” OR “affects”) AND ((“unobtrusive” OR “non-contact” OR “contact-free” OR “contact free”) AND (“sensors” OR “sensing”)) AND (“review” OR “literature review” OR “survey”) |
Fatigue | (“fatigue”) AND ((“unobtrusive” OR “non-contact” OR “contact-free” OR “contact free”) AND (“sensors” OR “sensing”)) |
Stress | (“stress”) AND ((“unobtrusive” OR “non-contact” OR “contact-free” OR “contact free”) AND (“sensors” OR “sensing”)) AND (“review” OR “literature review” OR “survey”) |
Social interactions | (“social interaction” OR “social relations” OR “relationships”) AND ((“unobtrusive” OR “non-contact” OR “contact-free” OR “contact free”) AND (“sensors” OR “sensing”)) |
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Sub-Dimension | No. of Articles After the Keyword Search | No. of Articles After the Screening |
---|---|---|
Affect | 55 | 6 |
Engagement | 98 | 7 |
Fatigue | 112 | 2 |
Stress | 32 | 3 |
Physical comfort | 176 | 3 |
Sleep deprivation | 34 | 8 |
Social interactions | 162 | 6 |
Sum | 644 | 35 |
Sub-Dimension | Behavioral Marker | Sensors | Relevant Literature |
---|---|---|---|
Affect | Facial expressions | RGB camera, microphone | [34,35] |
Speech | Microphone | [34,37] | |
Auricular positions | RGB camera | [38] | |
Facial temperature changes | Thermal camera | [39] | |
Eye movement and position | RGB camera, EOG signals | [45] | |
Engagement | Facial expressions | RGB camera, microphone array | [47,48,49,50,51,52] |
Posture | RGB camera, microphone array | [47,48] | |
Hand gestures | RGB camera | [47] | |
Upper-body motion | Depth camera | [53] | |
Gaze tracking and direction | RGB camera | [52] | |
Head rotation | RGB camera | [52] | |
Fatigue | Eye movement | Eye tracker | [54] |
Respiratory pattern | Radar | [55] | |
Stress | Body movements | Millimeter-wave sensor | [67] |
Activity information | WiFi-based localization system | [68] | |
Communication patterns | Smartphone | [69] | |
Phone usage | Smartphone | [69] | |
Location | Smartphone | [69] | |
Physical comfort | Posture | Inclinometer, RGB camera | [31,70] |
Hand and elbow movement | Wearable sleeve | [71] | |
Sleep deprivation | Eye blinking | RGB camera | [72,73,74] |
Distraction | RGB camera | [72] | |
Yawning | RGB camera | [57,72,73,74] | |
Head movement | RGB camera | [57,72] | |
Blink duration | Doppler sensor | [75] | |
Micro-sleep events | RGB camera | [74] | |
Nodding | RGB camera | [74] | |
Social interactions | Communication frequency | Microphone | [79] |
Category frequency | Microphone | [79] | |
Spoken conversations | Microphone | [77,78] | |
Duration of interaction | Microphone | [76] | |
Number and duration of phone calls | Smartphone | [80,81] | |
Number of SMSs | Smartphone | [81] |
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Anžur, Z.; Žinkovič, K.; Lukan, J.; Barbiero, P.; Slapničar, G.; Li, M.; Gjoreski, M.; Debus, M.E.; Trojer, S.; Luštrek, M.; et al. A Review of Methods for Unobtrusive Measurement of Work-Related Well-Being. Mach. Learn. Knowl. Extr. 2025, 7, 62. https://doi.org/10.3390/make7030062
Anžur Z, Žinkovič K, Lukan J, Barbiero P, Slapničar G, Li M, Gjoreski M, Debus ME, Trojer S, Luštrek M, et al. A Review of Methods for Unobtrusive Measurement of Work-Related Well-Being. Machine Learning and Knowledge Extraction. 2025; 7(3):62. https://doi.org/10.3390/make7030062
Chicago/Turabian StyleAnžur, Zoja, Klara Žinkovič, Junoš Lukan, Pietro Barbiero, Gašper Slapničar, Mohan Li, Martin Gjoreski, Maike E. Debus, Sebastijan Trojer, Mitja Luštrek, and et al. 2025. "A Review of Methods for Unobtrusive Measurement of Work-Related Well-Being" Machine Learning and Knowledge Extraction 7, no. 3: 62. https://doi.org/10.3390/make7030062
APA StyleAnžur, Z., Žinkovič, K., Lukan, J., Barbiero, P., Slapničar, G., Li, M., Gjoreski, M., Debus, M. E., Trojer, S., Luštrek, M., & Langheinrich, M. (2025). A Review of Methods for Unobtrusive Measurement of Work-Related Well-Being. Machine Learning and Knowledge Extraction, 7(3), 62. https://doi.org/10.3390/make7030062