Automatic Stress Classification With Pupil Diameter Analysis

Abstract

is an open access repository that collects the work of Arts et Métiers ParisTech researchers and makes it freely available over the web where possible. This article proposes a method based on wavelet transform and neural networks for relating pupillary behavior to psychological stress. The proposed method was tested by recording pupil diameter and electrodermal activity during a simulated driving task. Self-report measures were also collected. Participants performed a baseline run with the driving task only, followed by three stress runs where they were required to perform the driving task along with sound alerts, the presence of two human evaluators, and both. Self-reports and pupil diameter successfully indexed stress manipulation, and significant correlations were found between these measures. However, electrodermal activity did not vary accordingly. After training, the four-way parallel neural network classifier could guess whether a given unknown pupil diameter signal came from one of the four experimental trials with 79.2% precision. The present study shows that pupil diameter signal has good discriminating power for stress detection.

Assessment of ECG and respiration recordings from simulated emergency landings of ultra light aircraft

“…The most often and discussed in previous research are electrocardiogram (ECG), electroencephalogram (EEG), electrooculogram (EOG), electromyogram (EMG), electrodermal activity (EDA), blood pressure (BP), photoplethysmography (PPG), pupil diameter (PD), heart rate (HR), heart rate variability (HRV), skin temperature, and respiration belt 26–32 .…”

Effect of Closed-Loop Motion Cueing Algorithm for a Six-Degrees-of-Freedom Dynamic Simulator on Pupil Diameter as a Driver Stress Factor

“…Self-reports and PD data showed cognitive load influence, and also significant correlations were obtained between these measures. The study inferred that PD signal is an objective metric for cognitive workload detection [31].…”

“…A method based on wavelet transform and neural networks on pupillometry for mental stress was discussed in [31] during a simulated driving task. Self-reports and PD data showed cognitive load influence, and also significant correlations were obtained between these measures.…”

Scan Pattern for the Maritime Navigator

“…Eye Tracking data is used to compare a novice and experienced navigator (Forsman et al, 2012), and has also been used to study the effect of stress at the maritime bridge during a passage (Pedrotti, 2014). Eye tracking metrics showed a good potential in both evaluating novices vs experienced boat drivers, and in analyzing the effects of stress at the maritime bridge.…”