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Stress Tracker-Detecting Acute Stress From a Trackpad: Controlled Study.

Rahul Goel¹, Michael An^1,2, Hugo Alayrangues^1,3

¹Department of Radiology, School of Medicine, Stanford University, Palo Alto, CA, United States.

Journal of Medical Internet Research

|October 23, 2020

Summary

Detecting acute stress is possible using simple trackpad movements. This unobtrusive method offers a scalable and inexpensive approach to continuous health monitoring and early stress detection.

Keywords:

affective interfaces computer input device computer interaction mental health precision health stress sensing trackpad well-being

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Area of Science:

Biomedical Engineering
Human-Computer Interaction
Health Informatics

Background:

Stress poses significant risks to physiological and mental health.
Current stress monitoring methods lack convenience, affordability, and user adherence.
Previous research demonstrated acute stress detection via biomechanical analysis of computer input devices.

Purpose of the Study:

To investigate the feasibility of detecting acute stress using passive trackpad movement data.
To analyze three common trackpad interactions: click, steer, and drag and drop.
To extend prior work on mouse-based stress detection to trackpad interactions.

Main Methods:

Utilized biomechanical analysis of trackpad interactions.
Collected data from 18 participants performing click, steer, and drag and drop tasks under relaxed and stressed conditions.
Analyzed movement patterns and contact area during these interactions.

Main Results:

Increased mean and standard deviation of finger contact area during clicking under stress.
Demonstrated that as few as four trackpad clicks can accurately detect the presence of acute stress.
Identified significant differences in biomechanical parameters between stressed and relaxed states.

Conclusions:

Passive monitoring of computer trackpad usage offers a scalable and cost-effective solution for unobtrusive stress sensing.
Repurposing everyday computer interactions enables continuous health monitoring.
This approach supports proactive health interventions through early stress detection.