A State-Space Approach for Detecting Stress from Electrodermal Activity

Abstract

The human body responds to neurocognitive stress in multiple ways through its autonomic nervous system. Increases in heart rate, salivary cortisol and skin conductance level are often observed accompanying high levels of stress. Stress can also take on different forms including emotional, cognitive and motivational. While a precise definition for stress is lacking, a pertinent issue is to quantify the state of psychological stress manifested in the nervous system. State-space models have previously been applied to estimate an unobserved neural state (e.g. learning, consciousness) from physiological signal measurements and data collected during behavioral experiments. In this paper, we relate stress to the probability that a phasic driver impulse occurs in skin conductance signals. We apply state-space modeling to extracted binary measures to continuously track a stress level across episodes of cognitive and emotional stress as well as relaxation. Results demonstrate a promising approach for tracking stress through wearable devices.

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