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Investigating the Generalizability of Emotion Detection via Wearable Physiological Sensors: EmoWear Usecase

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F26%3A0199902" target="_blank" >RIV/00216305:26220/26:0199902 - isvavai.cz</a>

  • Result on the web

    <a href="http://dx.doi.org/10.1109/icumt67815.2025.11268739" target="_blank" >http://dx.doi.org/10.1109/icumt67815.2025.11268739</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1109/icumt67815.2025.11268739" target="_blank" >10.1109/icumt67815.2025.11268739</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Investigating the Generalizability of Emotion Detection via Wearable Physiological Sensors: EmoWear Usecase

  • Original language description

    Emotion detection is increasingly recognized as a foundational component in the evolution of intelligent eHealth systems. This paper presents a personalized methodology for identifying relevant physiological sensors for emotion recognition, using the open-access EmoWear dataset as a case study. The proposed framework applies statistical feature extraction and correlation analysis to examine the relationship between biosignals and emotional states, specifically valence, arousal, and dominance. The findings indicate that no single sensor modality universally correlates with emotional states across individuals, reinforcing the need for personalized and multimodal approaches. Notably, Electrodermal Activity (EDA) activity showed a higher correlation with valence, whereas Skin Temperature (SKT) was more closely associated with arousal; however, inter-individual variability remained significant. Overall, the analysis highlights challenges for generalizability in affective computing and emphasizes the importance of context and individual differences in emotion expression.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

  • OECD FORD branch

    20203 - Telecommunications

Result continuities

  • Project

  • Continuities

    S - Specificky vyzkum na vysokych skolach

Others

  • Publication year

    2025

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Article name in the collection

    2025 17th International Congress on Ultra Modern Telecommunications and Control Systems and Workshops (ICUMT)

  • ISBN

    979-8-3315-7675-2

  • ISSN

  • e-ISSN

  • Number of pages

    6

  • Pages from-to

    199-204

  • Publisher name

    IEEE

  • Place of publication

  • Event location

    Florence, Italy

  • Event date

    Nov 3, 2025

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article