Title
A Low-Cost Autonomous Attention Assessment System for Robot Intervention with Autistic Children
Abstract
Attention is an essential mental process that is important to achieve learning progress. We cannot get better in our academic learning unless we concentrate our attention on the person giving the educational material, such as the teacher or trainer. Children with Autism Spectrum Disorder (ASD) may have attention difficulties that can directly influence their academic skills. In recent years, robot intervention in autism therapy and assessment is becoming a popular research topic due to its role in enhancing children’s attention more than a regular human therapist, as well as, the increasing number of autism children compared to the availability of professional therapists. Robot intervention helps in reducing therapy time and makes early therapeutics sessions easier and much promising. Many researches have been conducted to develop robot intervention techniques for ASD children, and some methods have already been used to assess autistic individuals’ attention during the robot intervention sessions. Yet, the existing attention assessment methods are either very complex or simple with one measured interaction cue only. This paper presents a practical and low-cost automatic approach to assess autistic individuals’ attention during robot intervention; addressing multiple interaction cues. Experimental results show that the proposed attention assessment system could accurately measure the child attention and enhance therapy progress. This automatic attention system can open a new era for utilizing technologies to monitor students’ attentions in the class to enhance educational systems.
Year
DOI
Venue
2019
10.1109/EDUCON.2019.8725132
2019 IEEE Global Engineering Education Conference (EDUCON)
Keywords
Field
DocType
Cameras,Robot vision systems,Autism,Medical treatment,Hardware
Engineering,Robot,Multimedia
Conference
ISSN
ISBN
Citations 
2165-9567
978-1-5386-9506-7
0
PageRank 
References 
Authors
0.34
0
4
Name
Order
Citations
PageRank
Fady S. Alnajjar100.34
Abdulrahman Majed Renawi200.34
Massimiliano Cappuccio311.11
Omar Mubain400.34