Using sensors in the office to support self-management of well-being

Within SWELL, I focus on stress and well-being at work. What happens to us when we are distracted from work or feel time-pressure? Can we read from behavior whether someone is stressed? At TNO and RU Nijmegen we look at behavior with various sensors, like Kinect to inspect body postures, camera to look at facial expressions, body sensors to measure heart rate or skin conductance and computer logging to see activities on the computer. With machine learning we try to recognize behavior and get insights into the level of stress and well-being. To give the employee insight in his (work) behavior and how this relates to his or her well-being, we make visualizations of the data. To support the knowledge worker, we investigate the use of e-coaching to help employees self-manage their well-being. Stress from time to time for an important deadline is normal, but you should also de-stress and have healthy working patterns to prevent becoming burned out. 

Research topics

  • Combining work stress theory with possibilities of technology for behavior change at the workplace
  • Automatic recognition of mental states (mental effort, emotion, stress) on basis of unobtrusive sensors in the office
  • Insight into personal data by visualization

About Saskia Koldijk

Saskia has a bachelor and master’s degree in Artificial Intelligence (AI), which combines Computer Science with Psychology. I have an interest in integrating technical solutions with psychological theory. What I like most about AI is combining the strengths of a machine with the strengths of a human. Within SWELL I combine my expertise in Programming, Machine Learning, Visual Analytics and Human-Computer Interaction, with my knowledge of Cognitive Psychology, Work Psychology and Behavioral Change.

More information

Please visit Saskia's personal website here


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