Using Gaze Tracking on Sensory Integration Therapy for Eye-movement Detection
DOI:
https://doi.org/10.47611/jsrhs.v12i3.4947Keywords:
SIT, Autism Spectrum Disorder(ASD), Linear Regression, Analytic Hierarchy Process (AHP), Convolutional Neural Network (CNN)Abstract
Autism spectrum disorder is a condition that often occurs in infancy (from birth to three years old). A common problem includes eyesight disorders, where children cannot focus on a specific item. We use the method of Convolutional Neural Networks (CNN) to detect eyes and collect eye positions. Then, we use a linear regression model to best fit the movement of the eyeballs through the track of positions. After that, we use an Analytic Hierarchy Process (AHP) model for a multi-perspective judgment on children's performance in eye movement.
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Simonyan, K., & Zisserman, A. (2015). Very deep convolutional networks for large-scale image recognition. In Proceedings of the International Conference on Learning Representations (ICLR 2015). Retrieved from https://arxiv.org/abs/1409.1556
Antoinelame. “Antoinelame/Gazetracking:Eye Tracking Library Easily Implementable to Your Projects.” Github, https://github.com/antoinelame/GazeTracking.
James, G., Witten, D., Hastie, T., & Tibshirani, R. (2021). An Introduction to Statistical Learning: with Applications in R (Springer Texts in Statistics) (2nd ed. 2021). Springer.
Saaty, Thomas L. "Decision making with the analytic hierarchy process." International Journal of Services Sciences, vol. 1, no. 1, 2008, pp. 83-98. doi: 10.1504/IJSSCI.2008.017590.
“Data & amp; Statistics on Autism Spectrum Disorder.” Centers for Disease Control and Prevention, Centers for Disease Control and Prevention, 4 Apr. 2023, https://www.cdc.gov/ncbddd/autism/data.html.
Gopi, Ajay. “EECS at UC Berkeley.” To Send or to Not Send: A Case Study on Computer Vision for Low Power Edge Devices, EECS at UC Berkeley, May n.d., https://www2.eecs.berkeley.edu/Pubs/TechRpts/2020/EECS-2020-90.html.
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