A Stress Classification System Based on Arousal Analysis of the Nervous System

Abstract

Detection of an increment in stress levels is a step towards improving the quality of people’s lives, especially in the case of people with intellectual disabilities, as they have fewer resources to deal with this situation. This paper presents a biophysical stress classification system that is able to classify the detected stress situations at three intensity levels: low, medium and high. Furthermore, the system distinguishes between continued stress and a momentary alert depending on the subject’s arousal. The system uses two non-invasive physiological signals for the classification: the galvanic skin response and the heart rate variability. The experiment shows that the proposed system is able to detect and classify the different stress states achieving an accuracy of 97.5, % with a 0.9, % FN rate.