Key result
A pupillometry pipeline using an IR-sensitive webcam and Support Vector Machine was suitable for assessing stress and negative affect during stress-eliciting situations in a digital environment.
Why the study?
Can a pupillometry pipeline using an infrared-sensitive webcam detect stress and negative affect in remote working scenarios?
Can a pupillometry pipeline using an infrared-sensitive webcam detect stress and negative affect in remote working scenarios?
A novel pupillometry pipeline using IR-sensitive webcams can successfully detect stress and negative affect in digital environments.
Answers are grounded in this paper and cite their sources.
May support remote stress monitoring via webcam; leaves open validation before clinical use.
In this paper, we present a processing pipeline for the analysis of stress and negative affect based on pupillometry. We were able to show that it is possible to extract meaningful pupil features from video data recorded by an infrared- (IR-) sensitive webcam and successfully trained a Support Vector Machine on the corresponding dataset. Further, we conducted a study that shows that the proposed pipeline is suitable for the assessment of stress as well as negative affect during stress eliciting situations in a digital environment.
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Heimerl et al. (2022) studied Stress and negative affect. Pupillometry pipeline using IR-sensitive webcam and Support Vector Machine was evaluated on Detection of stress and negative affect. A pupillometry pipeline using an IR-sensitive webcam and Support Vector Machine was suitable for assessing stress and negative affect during stress-eliciting situations in a digital environment.
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