A preliminary visual system for assistant diagnosis of ASD

Autism spectrum disorder(ASD) is a kind of developmental disorder which attracted a lot of attention of researchers for its urgency and pervasiveness. The diagnosis and intervention of ASD is still complicated and hard to handle. The rapid development of technology has brought new methods to the auxiliary diagnosis of ASD, such as face detection, gaze estimation, action recognition, etc. The paper proposed a preliminary visual system for assistant diagnosis of ASD in a core clinical testing scenario-response to name. The eye center localization and gaze estimation were applied to measure the responses of the subject. The purpose of this paper is analyzing the feasibility of this system, and optimizing the sensing structure and the evaluation indicator.

[1]  B. Pennington,et al.  A theoretical approach to the deficits in infantile autism , 1991, Development and Psychopathology.

[2]  B. Rogé,et al.  Visual social attention in autism spectrum disorder: Insights from eye tracking studies , 2014, Neuroscience & Biobehavioral Reviews.

[3]  Wei Bao,et al.  Prevalence of Autism Spectrum Disorder Among US Children and Adolescents, 2014-2016 , 2018, JAMA.

[4]  Tony Charman,et al.  Why is joint attention a pivotal skill in autism? , 2003, Philosophical transactions of the Royal Society of London. Series B, Biological sciences.

[5]  Matthew S. Goodwin,et al.  Sensor-enabled detection of stereotypical motor movements in persons with autism spectrum disorder , 2008, IDC.

[6]  Agata Rozga,et al.  Measuring Child Visual Attention using Markerless Head Tracking from Color and Depth Sensing Cameras , 2014, ICMI.

[7]  E. Gordon,et al.  Brain maturation in adolescence: Concurrent changes in neuroanatomy and neurophysiology , 2007, Human brain mapping.

[8]  Li Xiaoli,et al.  A study of EEG and eye tracking in children with autism , 2018 .

[9]  Honghai Liu,et al.  Visual Focus of Attention Estimation Using Eye Center Localization , 2017, IEEE Systems Journal.

[10]  Niranjana Krupa,et al.  Recognition of emotions in autistic children using physiological signals , 2016 .

[11]  Jian-Wei Pan,et al.  Precision mapping the topological bands of 2D spin-orbit coupling with microwave spin-injection spectroscopy. , 2018, Science bulletin.

[12]  Honghai Liu,et al.  Gaze estimation driven solution for interacting children with ASD , 2015, 2015 International Symposium on Micro-NanoMechatronics and Human Science (MHS).

[13]  Wenbing Zhao,et al.  Technology-Facilitated Diagnosis and Treatment of Individuals with Autism Spectrum Disorder: An Engineering Perspective , 2017 .

[14]  Agata Rozga,et al.  A prospective study of response to name in infants at risk for autism. , 2007, Archives of pediatrics & adolescent medicine.

[15]  Ersilia M. DeFilippis,et al.  Open Osmosis: Library of Open Educational Resources (OER) for Medical Education , 2015 .

[16]  Z. Warren,et al.  Prevalence of autism spectrum disorder among children aged 8 years - autism and developmental disabilities monitoring network, 11 sites, United States, 2010. , 2014, Morbidity and mortality weekly report. Surveillance summaries.