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INTERNATIONAL JOURNAL OF SCIENTIFIC DEVELOPMENT AND RESEARCH International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2455-2631 | Impact factor: 8.15 | ESTD Year: 2016 open access , Peer-reviewed, and Refereed Journals, Impact factor 8.15 |
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| Paper Title: | AUTISM SPECTRUM DISORDER DETECTION IN CHILDREN USING COMPUTER VISION STRATEGIES |
| Authors Name: | M.NIRMALA , G. DHIVYA |
| Unique Id: | IJSDR2306093 |
| Published In: | Volume 8 Issue 6, June-2023 |
| Abstract: | Computer vision has been used to detect developmental abnormalities such as autism spectrum disorder (ASD).Computer vision used to pre diagnose various disorders. Facial analysis can be used to monitor vascular pulse, quantify discomfort, find facial paralysis, identify psychiatric problems, and use behavior imaging to distinguish people with ASD from those with normal development. We describe a technique for detecting an Autism's student level of engagement. Given the rise of distance learning in general and e-learning in particular, student participation is crucial and one of the most challenging issues for educators, academics, and policymakers. The main objective of the system is to monitor and determine the engagement of autism based student and their active participation during the E-learning session. We outline a method for assessing a student level of participation who has autism. It was created to work in real time and uses only information provided by the conventional built-in web-camera included in a laptop computer. We create a concentration index with three levels of engagement: "extremely engaged," "nominally involved," and "not engaged at all" by combining information on eye and head movements, as well as facial autism syndromes. The system was put to the test in a typical learning situation, and the findings demonstrate that it properly distinguishes "highly involved," "nominally engaged," and "not engaged at all" periods of time. Additionally, the results also show that the students with best scores also have higher concentration indexes. |
| Keywords: | Autism Spectrum Disorder, Behavior, Syndrome, student participation level, Computer Vision, Feature extraction. |
| Cite Article: | "AUTISM SPECTRUM DISORDER DETECTION IN CHILDREN USING COMPUTER VISION STRATEGIES", International Journal of Science & Engineering Development Research (www.ijsdr.org), ISSN:2455-2631, Vol.8, Issue 6, page no.627 - 636, June-2023, Available :http://www.ijsdr.org/papers/IJSDR2306093.pdf |
| Downloads: | 000337350 |
| Publication Details: | Published Paper ID: IJSDR2306093 Registration ID:207195 Published In: Volume 8 Issue 6, June-2023 DOI (Digital Object Identifier): Page No: 627 - 636 Publisher: IJSDR | www.ijsdr.org ISSN Number: 2455-2631 |
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