Computer Vision Techniques for Autism Symptoms Detection and Recognition: A Survey.
Sadek, E., AbdElSabour Seada, N., Ghoniemy, S. (2020). Computer Vision Techniques for Autism Symptoms Detection and Recognition: A Survey.. EKB Journal Management System, 20(2), 89-111. doi: 10.21608/ijicis.2020.46360.1034
Esraa Tarek Sadek; Noha Aly AbdElSabour Seada; Said Ghoniemy. "Computer Vision Techniques for Autism Symptoms Detection and Recognition: A Survey.". EKB Journal Management System, 20, 2, 2020, 89-111. doi: 10.21608/ijicis.2020.46360.1034
Sadek, E., AbdElSabour Seada, N., Ghoniemy, S. (2020). 'Computer Vision Techniques for Autism Symptoms Detection and Recognition: A Survey.', EKB Journal Management System, 20(2), pp. 89-111. doi: 10.21608/ijicis.2020.46360.1034
Sadek, E., AbdElSabour Seada, N., Ghoniemy, S. Computer Vision Techniques for Autism Symptoms Detection and Recognition: A Survey.. EKB Journal Management System, 2020; 20(2): 89-111. doi: 10.21608/ijicis.2020.46360.1034

Computer Vision Techniques for Autism Symptoms Detection and Recognition: A Survey.

International Journal of Intelligent Computing and Information Sciences
Article 14, Volume 20, Issue 2, December 2020, Page 89-111  XML PDF (708.43 K)
Document Type: Original Article
DOI: 10.21608/ijicis.2020.46360.1034
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Authors
Esraa Tarek Sadek email orcid 1; Noha Aly AbdElSabour Seada2; Said Ghoniemyorcid 3
1Computer Systems Department, Faculty of Computer and Information Sciences
2Lecturer at Faculty of Computer & Information Sciences, Computer Systems Department, Ain Shams University, Cairo , Egypt.
3Prof at Faculty of Computer & Information Sciences, Computer Systems Department, Ain Shams University, Cairo , Egypt.
Abstract
Autism spectrum disorder (ASD) is a world-threatening mental developing disorders that recently appeared widely, due to its diagnosis complexity as well as lack of evidence of its real causes. Many researchers have afforded great effort to precisely identify this syndrome and its symptoms. This survey provides a comprehensive study of autism spectrum disorder, its types, symptoms, prevalence, and developments in its diagnosing. Six categories for autism exposure and identification are currently investigated; clinical monitoring, genetics and blood analysis, Functional magnetic resonance imaging (fMRI), Electroencephalography (EEG) based investigation, wearable sensors and finally computer vision-based techniques. Computational technologies, especially computer-vision, machine learning and neural networks techniques have added great advances in detecting autism and these techniques are comprehensively reviewed in this paper. Also, medical assisting computer vision-based framework is proposed to detect observable autism symptoms. The proposed framework utilises recent and efficient techniques that can be used to produce accurate diagnosing results.
Keywords
Autism spectrum disorder; autistic symptoms detection; autism signs detection repetitive motor behaviours; autistic self-stimulatory or stereotypy behaviours; Computer Vision
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