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dc.contributor.authorBizzego, Andreaen_US
dc.contributor.authorGabrieli, Giulioen_US
dc.contributor.authorAzhari, Atiqahen_US
dc.contributor.authorSetoh, Peipeien_US
dc.contributor.authorEsposito, Gianlucaen_US
dc.contributor.editorA. Espositoen_US
dc.contributor.editorM. Faundez-Zanuyen_US
dc.contributor.editorF. C. Morabitoen_US
dc.contributor.editorE. Paseroen_US
dc.identifier.citationBizzego, A., Gabrieli, G., Azhari, A., Setoh, P. & Esposito, G. (2021). Computational methods for the assessment of empathic synchrony. A. Esposito, M. Faundez-Zanuy, F. C. Morabito & E. Pasero (Eds.), Progresses in Artificial Intelligence and Neural Systems (pp. 555-564). Springer Nature.
dc.description.abstractThe synchronization of physiological signals between persons is a well-known proxy of empathy. However, it is also influenced by physiological and environmental factors that should be discriminated to correctly characterize the empathy component. We discuss a framework to compute synchrony and introduce physynch, an open-source package developed to easily replicate its computational procedures. We adopted physynch to study the synchrony of the electrodermal activity in 61 male-female dyads with different types of relationship: strangers (18 dyads), friends (23 dyads) and lovers (20 dyads). The findings confirm previous results on Heart Rate Variability synchrony and suggest that synchrony is influenced by the type of relationship and is stronger in dyads of strangers. physynch is made available for download and use for researchers interested in measuring physiological synchrony.en_US
dc.publisherSpringer Natureen_US
dc.rights© The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021. All rights reserved.en_US
dc.subjectSocial sciences::Psychologyen_US
dc.titleComputational methods for the assessment of empathic synchronyen_US
dc.typeBook Chapteren_US
dc.contributor.schoolSchool of Social Sciencesen_US
dc.contributor.schoolLee Kong Chian School of Medicine (LKCMedicine)en_US
dc.contributor.organizationUniversity of Trento, Italyen_US
dc.description.versionAccepted versionen_US
dc.relation.ispartofbookProgresses in Artificial Intelligence and Neural Systemsen_US
dc.subject.keywordsPhysiological Synchronyen_US
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  Until 2023-07-17
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