A Systematic Literature Review on Affective Computing Techniques for Workplace Stress Detection

In a world where work significantly impacts daily life, its influence on well-being is undeniable. The prevalence of stress at work has gain an increased attention due to its profound effects on both individual health and corporate performance. Addressing and detecting stress has become an essential challenge in fostering a healthy work environment. Technological innovations, especially in the field of affective computing, which involves various IT resources for analyzing human behavior and emotions, offer promising solutions for measuring employee stress. This paper provides a Systematic Literature Review (SLR) focusing on the existing scientific research in stress at work assessment using affective computing technologies. What distinguishes our work from others is that we deeply focus on each phase of the stress quantification process. We start by reviewing application contexts, before detailing the data collection process, including data sources and collection devices. We then highlight data analysis techniques used in the literature. Finally, we emphasize the challenges discussed by researchers during their work and give insight into future work.