Gaze-Wasserstein: A Quantitative Screening Approach to Autism Spectrum Disorders

Kun Woo Cho1, Feng Lin2, Chen Song2, Xiaowei Xu3, Michelle Hartley-McAndrew2, Kathy Doody2, Wenyao Xu2

  • 1University at Buffalo
  • 2State University of New York, Buffalo
  • 3Huazhong University of Science and Technology

Details

Category

Contributed Papers (Oral)

Sessions

11:30 - 12:15 | Wed 26 Oct | Main Auditorium | WeBT1

Technical Session 2: The Role of Wireless in Improving Mental Health

Abstract

Early detection of children with autism spectrum disorder (ASD) has been of great interest to researchers due to an increase in the rate of autism incidence around the world. However, a diagnosis of ASD is still challenging to receive in a timely manner for the large-scale population because the current diagnostic practice requires considerable cost and time, and do not provide quantitative feedback. In this paper, we explore a new ASD screening method, namely Gaze-Wasserstein, that is non-invasive, fast, and widely accessible. Based on the gaze tracking and analysis, Gaze-Wasserstein is able to provide objective gaze pattern-based measurements for home-based ASD screening, and can eventually be deployed on any mobile technologies with a front camera. To test the performance of Gaze-Wasserstein, we conducted a pilot study with 32 child participants where 16 children have ASD and 16 children are typically developing. Evaluation results demonstrate the effectiveness and time-efficiency of our proposed method in the ASD screening, which indicate that our Gaze-Wasserstein is a promising autism screening approach in the clinical practice.

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