TY - GEN
T1 - A low-cost autonomous attention assessment system for robot intervention with autistic children
AU - Alnajjar, Fady S.
AU - Renawi, Abdulrahman Majed
AU - Cappuccio, Massimiliano
AU - Mubain, Omar
N1 - Publisher Copyright:
© 2019 IEEE.
PY - 2019/4
Y1 - 2019/4
N2 - 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.
AB - 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.
KW - Assessment system
KW - Autism diagnosis
KW - Autism therapy
KW - Nao robot
KW - Robot intervention
UR - http://www.scopus.com/inward/record.url?scp=85067496053&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85067496053&partnerID=8YFLogxK
U2 - 10.1109/EDUCON.2019.8725132
DO - 10.1109/EDUCON.2019.8725132
M3 - Conference contribution
AN - SCOPUS:85067496053
T3 - IEEE Global Engineering Education Conference, EDUCON
SP - 787
EP - 792
BT - Proceedings of 2019 IEEE Global Engineering Education Conference, EDUCON 2019
A2 - Schreiter, Sebastian
A2 - Ashmawy, Alaa K.
PB - IEEE Computer Society
T2 - 10th IEEE Global Engineering Education Conference, EDUCON 2019
Y2 - 9 April 2019 through 11 April 2019
ER -