Automatic Stress Classification With Pupil Diameter Analysis
Article dans une revue avec comité de lecture
Date
2014Journal
International Journal of Human-Computer InteractionAbstract
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.
Files in this item
Related items
Showing items related by title, author, creator and subject.
-
Navigation and interaction in a real-scale digital mock-up using natural language and user gesture Communication avec acteThis paper tries to demonstrate a very new real-scale 3D system and sum up some firsthand and cutting edge results concerning multi-modal navigation and interaction interfaces. This work is part of the CALLISTO-SARI ...
-
Communication sans acte3D systems due to its complicated electronical, mechanical and vision accessories have enormous degree of complexity both in design and evaluation. Navigation system usually plays an important role in most 3D ...
-
Communication avec acteThe paper proposes a method for estimating and predicting visually induced motion sickness (VIMS) occurring in a navigation task in a 3D immersive virtual environment, by extracting features from the body postural sway ...
-
Article dans une revue avec comité de lectureMIRZAEI, Mohammad Ali; OLIVER, James H.;
MERIENNE, Frédéric;
CHARDONNET, Jean-Rémy (Springer Verlag, 2014)
This paper presents a novel speak-to-VR virtual reality peripheral network (VRPN) server based on speech processing. The server uses a microphone array as a speech source and streams the results of the process through a ... -
Communication avec acteMIRZAEI, Mohammad Ali; PRIANTO, Sugeng; PÈRE, Christian;
MERIENNE, Frédéric;
CHARDONNET, Jean-Rémy (IEEE, 2013)
The paper presents a new mother wavelet adapted from a specific pattern. Wavelet multi-resolution analysis uses this wavelet to detect the position of the pattern in an Infra-Red (IR) signal under scale variation and the ...