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A Learning Agent for Stress Multi-Level Diagnostics, Personalised Stress Profiles and Interventions in the Work
Oliver Jung1, Mathias Schmoigl-Tonis1, Christoph Schranz1
1Salzburg Research Forschungsgesellschaft mbH, Salzburg, Austria.
Studies in Health Technology and Informatics
|April 24, 2025
Summary
The Relax project developed a stress management framework using continuous monitoring and personalized interventions. Future work will refine the system for better usability and effectiveness in managing work-related stress.
Area of Science:
- Occupational Health
- Digital Health
- Psychophysiology
Background:
- Work-related stress impacts 39% of Austrians, leading to depression and burnout.
- Key stressors include high workload and lack of control.
Purpose of the Study:
- Develop a holistic stress management framework.
- Implement continuous stress assessment and personalized interventions.
- Utilize physiological, behavioral, emotional, and cognitive indicators.
Main Methods:
- Longitudinal study design.
- Integration of wearable sensors (e.g., Polar Verity Sense).
- Combination of psychological methods and technical strategies.
Main Results:
- Usability challenges encountered due to technical issues.
- Positive reception of stress data visualization.
- Micro-Model showed good alignment with stress estimates; Macro-Model faced data limitations.
Conclusions:
- Individualized, multimodal stress management is crucial.
- System improvements and technical refinement are needed.
- Further validation using anonymized data is recommended.
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