A Survey on Sensor-Based Techniques for Continuous Stress Monitoring in Knowledge Work Environments

Prolonged work stress has an extensive negative impact on modern society. Recently, it has become an increasing issue, specifically in cognitively demanding knowledge-intensive professions. To address the global necessity of timely detection and reduction of work stress, sensor-based automated methods for measuring stress are emerging. Physiological and behavioral sensor data enable the potential for continuous stress detection, but challenges still exist concerning the effort required from the user and the sufficiency of available information, especially for models that want to adapt to personal traits and stress perceptions. This survey paper focuses on sensor-based stress recognition enabling continuous unobtrusive stress monitoring in the knowledge work environment, with a user acceptance and load suitable for sustainable long-term adoption. We provide an overview of the theoretical background of work stress and review the recent developments of sensor-based stress assessment, emphasizing real-world studies using physiological, behavioral, and environmental data. In addition, we discuss the applicability and challenges of different monitoring methods, including user acceptance. The presented survey provides insights into automating the assessment of work stress and related factors to advance the development of personalized well-being solutions based on pervasive data.