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Progresses in Artificial Intelligence and Neural Systems pp 435–475Cite as

Facial Emotion Recognition Skills and Measures in Children and Adolescents with Attention Deficit Hyperactivity Disorder (ADHD)

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Part of the book series: Smart Innovation, Systems and Technologies ((SIST,volume 184))

Abstract

Facial expressions have significant communicative functions; any changes in the facial muscles help disentangle meaning, control the conversational flow, provide information as to the speaker/listener’s emotional state and inform about intention. Abnormalities in the recognition of facial expressions have been associated with psychiatric disorders. This review focuses on facial recognition abilities in children and adolescents with Attention Deficit Hyperactivity Disorder (ADHD). Using PRISMA guidelines original articles published prior to August 2019 were identified focusing on the emotion recognition skills of children and adolescents with ADHD and the measures administered. 25 studies were identified with the majority (18) showing some deficits on emotion recognition in children/adolescents with ADHD compared to typically developing (TD) children. The results are synthesized in terms of the type of stimuli implicated (static vs. dynamic), the measures/tasks administered, whether authors differentiated among specific emotion dimensions in the analysis of results, the effect of comorbidity on emotion recognition, and whether greater deficits have been reported for some emotions compared to others. Studies on facial emotion recognition in children and adolescents with ADHD focused mainly on the recognition accuracy of facial emotions, showing inconsistent results and a heterogenous use of measures. It is unknown whether the studies’ participants followed therapeutic plans (other than pharmacotherapy) at the time of the study or before, a factor that may potentially have influenced the review’s results.

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Acknowledgements

The research leading to these results has received funding from the EU H2020 research and innovation program under grant agreement N. 769872 (EMPATHIC) and N. 823907 (MENHIR), the project SIROBOTICS that received funding from Italian MIUR, PNR 2015–2020, D.D. 1735, 13/07/ 2017, and the project ANDROIDS that received funding from Università della Campania “Luigi Vanvitelli” inside the program V:ALERE 2019, funded with D.R. 906 del 4/10/2019, prot. n. 157264,17/10/2019.

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  1. Dipartimento di Psicologia, Università Della Campania Luigi Vanvitelli, Caserta, Italy

    Aliki Economides, Massimiliano Conson & Anna Esposito

  2. Cyprus Neuroscience & Technology Institute, Nicosia, Cyprus

    Yiannis Laouris

  3. International Institute for Advanced Scientific Studies (IIASS), Vietri Sul Mare, Italy

    Anna Esposito

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  1. Dipartimento di Psicologia and IIASS, Università della Campania “Luigi Vanvitelli”, Caserta, Italy

    Anna Esposito

  2. Fundació Tecnocampus, Pompeu Fabra University, Mataró, Barcelona, Spain

    Marcos Faundez-Zanuy

  3. Department of Civil, Environmental, Energy, and Material Engineering, University Mediterranea of Reggio Calabria, Reggio Calabria, Italy

    Francesco Carlo Morabito

  4. Laboratorio di Neuronica, Dipartimento Elettronica e Telecomunicazioni , Politecnico di Torino, Torino, Italy

    Eros Pasero

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Economides, A., Laouris, Y., Conson, M., Esposito, A. (2021). Facial Emotion Recognition Skills and Measures in Children and Adolescents with Attention Deficit Hyperactivity Disorder (ADHD). In: Esposito, A., Faundez-Zanuy, M., Morabito, F., Pasero, E. (eds) Progresses in Artificial Intelligence and Neural Systems. Smart Innovation, Systems and Technologies, vol 184. Springer, Singapore. https://doi.org/10.1007/978-981-15-5093-5_39

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