Multimodal behavioral analysis for non-invasive stress detection

This study presents and approach to measure the levels of acute stress in humans by analysing their behavioral patterns when interacting with technological devices. We study the effects of stress on eight behavioral, physical and cognitive features. The data was collected with the participation of 19 users in different phases, with different levels of stress induced. A non-parametric statistical hypothesis test is used to determine which features show statistically significant differences, for each user, when under stress. It is shown that the features more related to stress are the acceleration and the mean and maximum intensity of the touch. It is also shown that each user is affected by stress in a specific way. Moreover, all the process of estimating stress is undertaken in a non-invasive way. This work constitutes the foundation of a context layer for a virtual environment for conflict resolution. The main objective is to overcome some of the main drawbacks of communicating online, namely the lack of contextual information such as body language or gestures.

► We monitor and estimate stress level using standard and non-invasive devices.
► We analyze computer-machine interaction patterns and behaviors.
► Stress does influence the way that we interact with devices.
► Touch intensity/duration, movement and acceleration show significant results.