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  4. Electrodermal Response Patterns and Emotional Engagement Under Continuous Algorithmic Video Stimulation: A Multimodal Biometric Analysis
 
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Electrodermal Response Patterns and Emotional Engagement Under Continuous Algorithmic Video Stimulation: A Multimodal Biometric Analysis

Journal
Technologies
ISSN
2227-7080
Date Issued
2026
Author(s)
Carolina Del-Valle-Soto
Violeta Corona
Jesus GomezRomero-Borquez
David Contreras-Tiscareno
Diego Sebastian Montoya-Rodriguez
Jesus Abel Gutierrez-Calvillo
Bernardo Sandoval
Varela Aldas, José
Centro de investigación en Mecatrónica y Sistemas Interactivos
Type
journal-article
DOI
10.3390/technologies14010070
URL
https://cris.indoamerica.edu.ec/handle/123456789/9925
Abstract
Excessive use of short-form video platforms such as TikTok has raised growing concerns about digital addiction and its impact on young users’ emotional well-being. This study examines the relationship between continuous TikTok exposure and emotional engagement in young adults aged 20–23 through a multimodal experimental design. The purpose of this research is to determine whether emotional engagement increases, remains stable, or declines during prolonged exposure and to assess the degree of correspondence between facially inferred engagement and physiological arousal. To achieve this, multimodal biometric data were collected using the iMotions platform, integrating galvanic skin response (GSR) sensors and facial expression analysis via Affectiva’s AFFDEX SDK 5.1. Engagement levels were binarized using a logistic transformation, and a binomial test was conducted. GSR analysis, merged with a 50 ms tolerance, revealed no significant differences in skin conductance between engaged and non-engaged states. Findings indicate that although TikTok elicits strong initial emotional engagement, engagement levels significantly decline over time, suggesting habituation and emotional fatigue. The results refine our understanding of how algorithm-driven, short-form content affects users’ affective responses and highlight the limitations of facial metrics as sole indicators of physiological arousal. Implications for theory include advancing multimodal models of emotional engagement that account for divergences between expressivity and autonomic activation. Implications for practice emphasize the need for ethical platform design and improved digital well-being interventions. The originality and value of this study lie in its controlled experimental approach that synchronizes facial and physiological signals, offering objective evidence of the temporal decay of emotional engagement during continuous TikTok use and underscoring the complexity of measuring affect in highly stimulating digital environments.
Subjects
  • affective computing

  • electrochemical biose...

  • electrodermal activit...

  • physiological signal ...

  • skin conductance

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