IMITASD: Imitation Assessment Model for Children with Autism Based on Human Pose Estimation

Hany Said, Khaled Mahar, Shaymaa E. Sorour (), Ahmed Elsheshai, Ramy Shaaban, Mohamed Hesham, Mustafa Khadr, Youssef A. Mehanna, Ammar Basha and Fahima A. Maghraby
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Hany Said: College of Artificial Intelligence, Arab Academy for Science, Technology, and Maritime Transport, El Alamein 51718, Egypt
Khaled Mahar: Arab Center for Artificial Intelligence, Arab Academy for Science, Technology, and Maritime Transport, Alexandria 21532, Egypt
Shaymaa E. Sorour: Department of Management Information Systems, School of Business, King Faisal University, Alhufof 31982, Saudi Arabia
Ahmed Elsheshai: College of Medicine, Arab Academy for Science, Technology, and Maritime Transport, El Alamein 51718, Egypt
Ramy Shaaban: Department of Instructional Technology and Learning Sciences, Utah State University, Salt Lake City, UT 84322, USA
Mohamed Hesham: College of Medicine, Arab Academy for Science, Technology, and Maritime Transport, El Alamein 51718, Egypt
Mustafa Khadr: Research and Innovation Center, Arab Academy for Science, Technology, and Maritime Transport, El Alamein 51718, Egypt
Youssef A. Mehanna: Research and Innovation Center, Arab Academy for Science, Technology, and Maritime Transport, El Alamein 51718, Egypt
Ammar Basha: Research and Innovation Center, Arab Academy for Science, Technology, and Maritime Transport, El Alamein 51718, Egypt
Fahima A. Maghraby: College of Computing and Information Technology, Arab Academy for Science, Technology, and Maritime Transport, Cairo 2033, Egypt

Mathematics, 2024, vol. 12, issue 21, 1-25

Abstract: Autism is a challenging brain disorder affecting children at global and national scales. Applied behavior analysis is commonly conducted as an efficient medical therapy for children. This paper focused on one paradigm of applied behavior analysis, imitation, where children mimic certain lessons to enhance children’s social behavior and play skills. This paper introduces IMITASD, a practical monitoring assessment model designed to evaluate autistic children’s behaviors efficiently. The proposed model provides an efficient solution for clinics and homes equipped with mid-specification computers attached to webcams. IMITASD automates the scoring of autistic children’s videos while they imitate a series of lessons. The model integrates two core modules: attention estimation and imitation assessment. The attention module monitors the child’s position by tracking the child’s face and determining the head pose. The imitation module extracts a set of crucial key points from both the child’s head and arms to measure the similarity with a reference imitation lesson using dynamic time warping. The model was validated using a refined dataset of 268 videos collected from 11 Egyptian autistic children during conducting six imitation lessons. The analysis demonstrated that IMITASD provides fast scoring, takes less than three seconds, and shows a robust measure as it has a high correlation with scores given by medical therapists, about 0.9, highlighting its effectiveness for children’s training applications.

Keywords: autism; imitation; attention; MediaPipe; dynamic time warping; human pose estimation (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2024
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