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| Autores principales: | , , , , , , , , , , |
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| Formato: | Preprint |
| Publicado: |
2025
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| Materias: | |
| Acceso en línea: | https://arxiv.org/abs/2504.13886 |
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| _version_ | 1866914259508658176 |
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| author | Pansara, Zeel Navyte, Gabriele Freitas-Mendes, Tatiana Bottger, Camila Franco, Edoardo Citi, Luca Jacobi, Erik S. Poerio, Giulia L. Gillmeister, Helge Cinel, Caterina De Feo, Vito |
| author_facet | Pansara, Zeel Navyte, Gabriele Freitas-Mendes, Tatiana Bottger, Camila Franco, Edoardo Citi, Luca Jacobi, Erik S. Poerio, Giulia L. Gillmeister, Helge Cinel, Caterina De Feo, Vito |
| contents | Pupil dilation is recognized as an objective indicator of emotional arousal, but confounding factors such as the luminosity of stimuli and the surrounding environment have greatly limited its practical usefulness. This study presents a new approach to isolate and remove the effect of luminosity on pupil dilation. We validated this approach by showing 32 video clips with different content and emotional intensity to 47 participants, who reported their level of emotional arousal after each video. We developed a model capable of predicting the effect of luminosity on pupil size as a function of screen brightness, which adapts to individual physiological differences and different types of monitors through a brief pre-experimental calibration. We thus estimated the pupil size due exclusively to luminosity and subtracted it from the total recorded pupil size, obtaining the component due exclusively to arousal. From the latter, we predicted the arousal of each participant for each video using two models. We first used a simple linear regression model. When we used the luminosity-corrected pupil size, we obtained a correlation between predicted and self-reported arousal of r = 0.65 +/- 0.12, and R2 of 0.43 +/- 0.12. The uncorrected pupil size, instead, showed virtually no predictive power (r = 0.26 +/- 0.15, R2 = 0.09 +/- 0.089). We then used an Extreme Gradient Boosting model, obtaining even better results in the case of luminosity correction (r = 0.765 +/- 0.047, R2 = 0.556 +/- 0.085). Our results highlight that separating emotional and luminosity components from pupillary responses is crucial for accurately predicting arousal. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2504_13886 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Quantifying Emotional Arousal through Pupillary Response: A Novel Approach for Isolating the Luminosity Effect and Predicting Affective States Pansara, Zeel Navyte, Gabriele Freitas-Mendes, Tatiana Bottger, Camila Franco, Edoardo Citi, Luca Jacobi, Erik S. Poerio, Giulia L. Gillmeister, Helge Cinel, Caterina De Feo, Vito Human-Computer Interaction Pupil dilation is recognized as an objective indicator of emotional arousal, but confounding factors such as the luminosity of stimuli and the surrounding environment have greatly limited its practical usefulness. This study presents a new approach to isolate and remove the effect of luminosity on pupil dilation. We validated this approach by showing 32 video clips with different content and emotional intensity to 47 participants, who reported their level of emotional arousal after each video. We developed a model capable of predicting the effect of luminosity on pupil size as a function of screen brightness, which adapts to individual physiological differences and different types of monitors through a brief pre-experimental calibration. We thus estimated the pupil size due exclusively to luminosity and subtracted it from the total recorded pupil size, obtaining the component due exclusively to arousal. From the latter, we predicted the arousal of each participant for each video using two models. We first used a simple linear regression model. When we used the luminosity-corrected pupil size, we obtained a correlation between predicted and self-reported arousal of r = 0.65 +/- 0.12, and R2 of 0.43 +/- 0.12. The uncorrected pupil size, instead, showed virtually no predictive power (r = 0.26 +/- 0.15, R2 = 0.09 +/- 0.089). We then used an Extreme Gradient Boosting model, obtaining even better results in the case of luminosity correction (r = 0.765 +/- 0.047, R2 = 0.556 +/- 0.085). Our results highlight that separating emotional and luminosity components from pupillary responses is crucial for accurately predicting arousal. |
| title | Quantifying Emotional Arousal through Pupillary Response: A Novel Approach for Isolating the Luminosity Effect and Predicting Affective States |
| topic | Human-Computer Interaction |
| url | https://arxiv.org/abs/2504.13886 |