Realization of stress detection using psychophysiological signals for improvement of human-computer interactions

It has been suggested that effectively detecting the stress level of a computer user could possibly develop the computers' ability to respond intelligently and help the user relax from negative emotional states during human-computer interaction. Our research focuses on the use of three physiological signals: blood volume pulse (BVP), galvanic skin response (GSR) and pupil diameter (PD), to automatically monitor the stress state of computer users. This paper reports on the hardware and software instrumentation development and signal processing approach used to detect changes in the stress level of a subject interacting with a computer, within the framework of a specific experimental task. For this experiment a computer game was implemented on the basis of a clinical mental stress test, called the 'Stroop Test', adapted to make the subject experience two different levels of stress, while his/her BVP, GSR and PD signals were continuously recorded Several data processing techniques were applied to extract effective attributes of the 'stress' state of the subjects. Current results indicate that there exists a strong correlation among changes in those three signals and the shift in the emotional states when stress stimuli are applied to the interaction environment.