A computer mouse for stress identification of older adults at work

Abstract

Stress is an unpleasant condition that entails negative emotions such as fear, worry and nervousness. Motivated by existing research that accompanies stress with physical reactions like increased heart rate, blood volume, pupil dilation and skin conductance, this work builds on the premise that measuring such reactions in real-time could implicitly identify stress of older adults at work while interacting with a system. For this purpose, an inhouse computer mouse was built with embedded sensors for measuring the users' heart rate, skin conductance, skin temperature, and grip force. We have developed a probabilistic classification algorithm that receives as input these physiological measurements, and accordingly identifies emotional stress events. This work contributes to a large body of research in user modeling, aiming to identify when computer users are stressed, and accordingly provide intelligent interventions and personalized solutions to help reduce their frustration and prevent negative health conditions.