Applying Eye Tracking to Identify Autism Spectrum Disorder in Children
- 563 Downloads
Eye tracking (ET) holds potential for the early detection of autism spectrum disorder (ASD). To overcome the difficulties of working with young children, developing a short and informative paradigm is crucial for ET. We investigated the fixation times of 37 ASD and 37 typically developing (TD) children ages 4–6 watching a 10-second video of a female speaking. ASD children showed significant reductions in fixation time at six areas of interest. Furthermore, discriminant analysis revealed fixation times at the mouth and body could significantly discriminate ASD from TD with a classification accuracy of 85.1%, sensitivity of 86.5%, and specificity of 83.8%. Our study suggests that a short video clip may provide enough information to distinguish ASD from TD children.
KeywordsAutism Eye tracking Fixation time Machine learning Face
GW, XK, YL, JK contributes experimental design; GW, BS, YL, ZW, ZF contributes data collection; SY, YT, BS, MK contributes data analysis; JK, SY, GW, XK, YT, JP, CL contributes manuscript preparation.
This study was funded by Sanming Project of Medicine in Shenzhen (SZSM201512009). JK is supported by R01 AT008563, R21AT008707, and R61AT009310 from NIH/NCCIH.
Compliance with Ethical Standards
Conflict of interest
JK has a disclosure to report (holding equity in a startup company (MNT) and pending patents to develop new neuromodulation tools) but declares no conflict of interest. All other authors declare no conflict of interest.
All procedures performed in studies involving human participants were in accordance with the ethical standards of the Shenzhen Maternity & Child Healthcare Hospital research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.
Informed consent was obtained from parents of all individual participants included in the study. We are grateful to Georgia J Wilson for her help in revising the manuscript.
- Bolte, S., Bartl-Pokorny, K. D., Jonsson, U., Berggren, S., Zhang, D., Kostrzewa, E., … Marschik, P. B. (2016). How can clinicians detect and treat autism early? Methodological trends of technology use in research. Acta Paediatrica, 105(2), 137–144. https://doi.org/10.1111/apa.13243.CrossRefGoogle Scholar
- Council on Children With Disabilities, Section on Developmental Behavioral Pediatrics, Bright Futures Steering Committee, & Medical Home Initiatives for Children With Special Needs Project Advisory Committee (2006). Identifying infants and young children with developmental disorders in the medical home: An algorithm for developmental surveillance and screening. Pediatrics, 118(1), 405–420. https://doi.org/10.1542/peds.2006-1231.CrossRefGoogle Scholar
- Crippa, A., Marzocchi, G. M., Piroddi, C., Besana, D., Giribone, S., Vio, C., … Sora, M. L. (2015). An integrated model of executive functioning is helpful for understanding ADHD and associated disorders. Journal of Attention Disorders, 19(6), 455–467. https://doi.org/10.1177/1087054714542000.CrossRefGoogle Scholar
- Falck-Ytter, T., Fernell, E., Hedvall, A. L., von Hofsten, C., & Gillberg, C. (2012). Gaze performance in children with autism spectrum disorder when observing communicative actions. Journal of Autism and Developmental Disorders, 42(10), 2236–2245. https://doi.org/10.1007/s10803-012-1471-6.CrossRefGoogle Scholar
- Frazier, T. W., Strauss, M., Klingemier, E. W., Zetzer, E. E., Hardan, A. Y., Eng, C., & Youngstrom, E. A. (2017). A meta-analysis of gaze differences to social and nonsocial information between individuals with and without autism. Journal of the American Academy of Child & Adolescent Psychiatry, 56(7), 546–555. https://doi.org/10.1016/j.jaac.2017.05.005.CrossRefGoogle Scholar
- Fujioka, T., Inohara, K., Okamoto, Y., Masuya, Y., Ishitobi, M., Saito, D. N., … Kosaka, H. (2016). Gazefinder as a clinical supplementary tool for discriminating between autism spectrum disorder and typical development in male adolescents and adults. Molecular Autism, 7, 19. https://doi.org/10.1186/s13229-016-0083-y.CrossRefGoogle Scholar
- Fujisawa, T. X., Tanaka, S., Saito, D. N., Kosaka, H., & Tomoda, A. (2014). Visual attention for social information and salivary oxytocin levels in preschool children with autism spectrum disorders: An eye-tracking study. Frontiers in Neuroscience, 8, 295. https://doi.org/10.3389/fnins.2014.00295.CrossRefGoogle Scholar
- Jones, W., Carr, K., & Klin, A. (2008). Absence of preferential looking to the eyes of approaching adults predicts level of social disability in 2-year-old toddlers with autism spectrum disorder. Archives of General Psychiatry, 65(8), 946–954. https://doi.org/10.1001/archpsyc.65.8.946.CrossRefGoogle Scholar
- Moody, E. J., Reyes, N., Ledbetter, C., Wiggins, L., DiGuiseppi, C., Alexander, A., … Rosenberg, S. A. (2017). Screening for autism with the SRS and SCQ: Variations across demographic, developmental and behavioral factors in preschool children. Journal of Autism and Developmental Disorders, 47(11), 3550–3561. https://doi.org/10.1007/s10803-017-3255-5.CrossRefGoogle Scholar
- Scarpa, A., Reyes, N. M., Patriquin, M. A., Lorenzi, J., Hassenfeldt, T. A., Desai, V. J., & Kerkering, K. W. (2013). The modified checklist for autism in toddlers: Reliability in a diverse rural American sample. Journal of Autism and Developmental Disorders, 43(10), 2269–2279. https://doi.org/10.1007/s10803-013-1779-x.CrossRefGoogle Scholar
- Sterling, L., Dawson, G., Webb, S., Murias, M., Munson, J., Panagiotides, H., & Aylward, E. (2008). The role of face familiarity in eye tracking of faces by individuals with autism spectrum disorders. Journal of Autism and Developmental Disorders, 38(9), 1666–1675. https://doi.org/10.1007/s10803-008-0550-1.CrossRefGoogle Scholar
- Zhang, X., Li, J., Qin, M., & Zhang, C. (1994). The revise of Gesell Developmental Scale on 3.5–6 years of age in Beijing. Chinese Journal of Clinical Psychology, 2(3), 148–150.Google Scholar