Unravelling the Robot Gestures Interpretation by Children with Autism Spectrum Disorder During Human-Robot Interaction

  1. Benedicto, Gema 12
  2. Juan, Carlos G. 12
  3. Fernández-Caballero, Antonio 3
  4. Fernandez, Eduardo 24
  5. Ferrández, Jose Manuel 1
  1. 1 Universidad Politécnica de Cartagena
    info

    Universidad Politécnica de Cartagena

    Cartagena, España

    ROR https://ror.org/02k5kx966

  2. 2 Universidad Miguel Hernández de Elche
    info

    Universidad Miguel Hernández de Elche

    Elche, España

    ROR https://ror.org/01azzms13

  3. 3 Universidad de Castilla-La Mancha
    info

    Universidad de Castilla-La Mancha

    Ciudad Real, España

    ROR https://ror.org/05r78ng12

  4. 4 CIBER BBN, 03202, Elche (Alicante), Spain
Erakutsi afiliazioak +
Liburua:
Artificial Intelligence for Neuroscience and Emotional Systems

ISSN: 0302-9743,  1611-3349

ISBN: 978-3-031-61139-1,  978-3-031-61140-7

Argitalpen urtea: 2024

Orrialdeak: 342-355

Mota: Liburuko kapitulua

DOI: 10.1007/978-3-031-61140-7_33 GOOGLE SCHOLAR

Laburpena

The ability to interpret and respond to nonverbal signals is crucial in human-robot interaction. This enables the establishment of effective communication and a meaningful relationship between the robot and the user. Understanding the importance of nonverbal communication is a fundamental aspect in the design of therapeutic and technological interventions for individuals with Autism Spectrum Disorder (ASD). This study investigates how children with Autism Spectrum Disorder (ASD) interpret and respond to gestures made by robots, particularly focusing on the humanoid robot Pepper and the use of tablets, with the aim of enhancing human-robot interactions for the development of more effective therapies for ASD. Participants, both with and without ASD, engaged in sessions involving nonverbal and verbal communication scenarios with the robot and instructor. Results indicate significant differences in gesture recognition between children with ASD and neurotypical children, especially in conditions involving verbal communication. This approach aids in improving interventions, increasingly individualized and effective. Further research with larger samples and improved robot autonomy is warranted to enhance therapeutic outcomes and address limitations encountered in this study.

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