• DocumentCode
    589112
  • Title

    Robotic Social Therapy on Children with Autism: Preliminary Evaluation through Multi-parametric Analysis

  • Author

    Mazzei, Daniele ; Greco, Alberto ; Lazzeri, Nicole ; Zaraki, Abolfazl ; Lanata, Antonio ; Igliozzi, Roberta ; Mancini, Alice ; Stoppa, Francesca ; Scilingo, Enzo Pasquale ; Muratori, Filippo ; De Rossi, Danilo

  • fYear
    2012
  • fDate
    3-5 Sept. 2012
  • Firstpage
    766
  • Lastpage
    771
  • Abstract
    Autism Spectrum Disorder (ASD) is a neural development disorder characterized by specific patterns of behavioral and social difficulties. Beyond these core symptoms, additional problems such as absence of gender differences identification, interactional distortions of environmental and family responses are often present. Taking into account these emotional and behavioral problems researchers and clinicians are focusing on the design of innovative therapeutic approaches aimed to improve social capabilities of subjects with ASD. Thanks to the technological and scientific progresses of the last years, nowadays it is possible to create human-like robots with social and emotional capabilities. Furthermore it is also possible to analyze physiological signals inferring subjects´ psycho-physiological state which can be compared with a behavioral analysis in order to obtain a deeper understanding of subjects reactions to treatments. In this work a preliminary evaluation of an innovative social robot-based treatment for subjects with ASD is described. The treatment consists in a complex stimulation and acquisition platform composed of a social robot, a multi-parametric acquisition system and a therapeutic protocol. During the preliminary tests of the treatment the subject´s physiological signals and behavioral parameters have been recorded and used together with the therapists´ annotations to infer the subjects´ induced reactions. Physiological signals were analyzed and statistically evaluated demonstrating the possibility to correctly discern the two groups (ASD and normally developing subjects) with a classification percentage higher than 92%. Statistical analysis also highlighted the treatment capability to induce different affective states in subjects with ASDs more than in control subjects, demonstrating that the treatment is well designed and tuned on ASDs deficits and behavioral lacks.
  • Keywords
    Face; Feature extraction; Humanoid robots; Physiology; Protocols; Variable speed drives; Autism Spectrum Disorder; Gesture Recognition; Human-Robot interaction; Pattern Recognition; Physiological Signals; Scene Analysis; Social Robot; Statistics;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Privacy, Security, Risk and Trust (PASSAT), 2012 International Conference on and 2012 International Confernece on Social Computing (SocialCom)
  • Conference_Location
    Amsterdam, Netherlands
  • Print_ISBN
    978-1-4673-5638-1
  • Type

    conf

  • DOI
    10.1109/SocialCom-PASSAT.2012.101
  • Filename
    6406398