Robotic social, therapy on children with autism: Preliminary evaluation through multi-parametric analysis

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

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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.

Original languageEnglish
Title of host publicationProceedings - 2012 ASE/IEEE International Conference on Privacy, Security, Risk and Trust and 2012 ASE/IEEE International Conference on Social Computing, SocialCom/PASSAT 2012
Pages766-771
Number of pages6
DOIs
Publication statusPublished - 2012
Event2012 ASE/IEEE International Conference on Social Computing, SocialCom 2012 and the 2012 ASE/IEEE International Conference on Privacy, Security, Risk and Trust, PASSAT 2012 - Amsterdam, Netherlands
Duration: Sep 3 2012Sep 5 2012

Other

Other2012 ASE/IEEE International Conference on Social Computing, SocialCom 2012 and the 2012 ASE/IEEE International Conference on Privacy, Security, Risk and Trust, PASSAT 2012
Country/TerritoryNetherlands
CityAmsterdam
Period9/3/129/5/12

Keywords

  • Autism Spectrum Disorder
  • Gesture Recognition
  • Human-Robot interaction
  • Pattern Recognition
  • Physiological Signals
  • Scene Analysis
  • Social Robot
  • Statistics

ASJC Scopus subject areas

  • Safety, Risk, Reliability and Quality

Fingerprint

Dive into the research topics of 'Robotic social, therapy on children with autism: Preliminary evaluation through multi-parametric analysis'. Together they form a unique fingerprint.

Cite this