Hi, I was reading some to papers that use machine-learning approaches in automated emotion classification tasks, but they don’t specify which eye-tracking variables are the most informative to successfully infer the person’s affective state.
I would like that anyone recommend me papers (articles, books or chapters) that report associations between other eye-tracking measures, (besides pupil size, e.g. fixation duration, saccades, blinks, etc.) and affective variables (valence, arousal, or specific emotions)?
Hi Rogrigo, I think this article might help you out: Article Emotion Recognition Using Eye-Tracking: Taxonomy, Review and...
Hi Marian Sauter , thanks for your answer. I was followed Zheng's team work, and its very interesting, they focus in accuracy of classification using machine learning... but they do not report which characteristics are regularities for each emotion/emotion dimension. And the same happens with other experimental studies that use algorithm for emotion classification. It's so curious.
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