Paper Info
Title
Robotic Social Therapy on Children with Autism: Preliminary Evaluation through Multi-parametric Analysis
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.
Year
DOI
Venue
2012
10.1109/SocialCom-PASSAT.2012.99
SocialCom/PASSAT
Keywords
DocType
Citations 
feature extraction,neurophysiology,face,humanoid robots,physiology,protocols,statistical analysis,human robot interaction
Conference
0
PageRank 
References 
Authors
0.34
8
11
Name
Order
Citations
PageRank
Daniele Mazzei19915.00
Alberto Greco2588.58
Nicole Lazzeri3152.89
Abolfazl Zaraki4599.20
Antonio Lanatà5808.37
Roberta Igliozzi600.34
Alice Mancini791.20
Francesca Stoppa800.34
Enzo Pasquale Scilingo939498.07
Filippo Muratori10676.16
Danilo De Rossi1131155.41