Ali ,Sara

Multi-Robot Interactive Therapy for Children with Autism Spectrum Disorder / Sara Ali - 139p. Soft Copy 30cm

Robot-Assisted Therapies (RAT) is an emerging field and has shown promising results. Recently, one
of the prominent applications of robots is assistive therapy is for Autism Spectrum Disorder (ASD).
Autism Spectrum Disorder is a set of neurodevelopment disorder affecting 7.5 million people around
the world. Children with ASD lack social and communication skills which affects their ability in
schools as well as in community. Recently, humanoid robots are used for the treatment of children
with autism spectrum disorder to improve the development of communicational, behavioral, motor
movements, joint attention, and physical behaviors. These interactive interventions that use robots for
children with ASD, is one of the favorable tools for improving the behavior of children. In particular,
the area of robotics is helping a lot in the treatment of ASD as the robot acts as a mediator as well as
measures the response of an autistic child. However, the research aiming that the treatment of children
with autism is limited, these therapies introduced by robots are successful in establishing basic
communication skills. This research has proposed a novel mathematical model for an adaptive therapy
of children with Autism Spectrum Disorder called Multi-robot-mediated Intervention System (MRIS).
Three different therapies related to improvement in joint attention and imitation skills, effective
human-human interaction and comparison of effective stimulus are introduced under this mathematical
model. This research aims to introduce multi-sensory data that provides the quantitative support for
improvement in social skills of children with autism, replacing the current techniques of measuring the
improvement from physically observing the ASD child and with video analysis. Besides ensuring the
accuracy in results, this method also introduces consistency as robots are immune to fatigue, unlike
humans. The effectiveness of the model has been validated using cognitive brain state of the children
with Electroencephalogram (EEG) neuroheadsets. Moreover, the effectiveness of the results has been
validated using statistical analysis and the Childhood Autism Rating Scale (CARS).


PhD Robotics and Intelligent Machine Engineering

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