Detecting Stress in the Office From How People Type and Click

hubie writes:

Researchers at ETH Zurich have developed a model that detects workplace stress just by how people type and move their computer mouse:

In Switzerland, one in three employees suffers from workplace stress. Those affected often don't realise that their physical and mental resources are dwindling until it's too late. This makes it all the more important to identify work-related stress as early as possible where it arises: in the workplace.

Researchers at ETH Zurich are now taking a crucial step in this direction. Using new data and machine learning, they have developed a model that can tell how stressed we are just from the way we type and use our mouse.

And there's more: "How we type on our keyboard and move our mouse seems to be a better predictor of how stressed we feel in an office environment than our heart rate," explains study author Mara Nagelin, a mathematician who conducts research at the Chair of Technology Marketing and the Mobiliar Lab for Analytics at ETH Zurich. Applied correctly, these findings could be used in future to prevent increased stress in the workplace early on.

[...] The researchers are currently testing their model with data from Swiss employees who have agreed to have their mouse and keyboard behaviour as well as their heart data recorded directly at their workplace using an app. The same app also regularly asks the employees about their subjective stress levels. Results should be available by the end of the year.

However, workplace stress detection also raises some thorny issues: "The only way people will accept and use our technology is if we can guarantee that we will anonymise and protect their data. We want to help workers to identify stress early, not create a monitoring tool for companies," Kerr says. In another study involving employees and ethicists, the researchers are investigating which features an app needs to have to meet these requirements and ensure responsible handling of sensitive data.

Journal Reference:
Naegelin M, Weibel RP, Kerr JI, Schinazi VP, et al.: An interpretable machine learning approach to multimodal stress detection in a simulated office environment. Journal of Biomedical Informatics 2023, 139: 104299, doi: https://doi.org/10.1016/j.jbi.2023.104299

Original Submission

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