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• Autism Detection Based on Eye Movement Sequences on the Web: A Scanpath Trend Analysis Approach

  Sukru Eraslan, Yeliz Yesilada, Victoria Yaneva, Simon Harper · 2020 · Proceedings of the 17th International Web for All Conference (W4A)

  This paper investigates whether sequential eye-movement data — the order in which people look at elements on web pages — can be used to detect autism, improving upon the authors' previous non-sequential approach that achieved 75% accuracy but was unstable across different web…

  autism · eye tracking · machine learning · web accessibility · scanpath analysis

• Supporting the Design of Data Visualisation for the Visually Impaired through Reinforcement Learning

  Dalal Aljasem · 2020 · Proceedings of the 17th International Web for All Conference (W4A)

  This doctoral consortium paper presents a research programme aimed at making data visualizations more accessible to people with partial vision loss, specifically those with peripheral vision damage (tunnel vision from conditions like glaucoma) or central vision loss (from…

  data visualization · visual impairment · reinforcement learning · visual search · machine learning

• Eyelid Gestures on Mobile Devices for People with Motor Impairments

  Mingming Fan, Zhen Li, Franklin Mingzhe Li · 2020 · Proceedings of the 22nd International ACM SIGACCESS Conference on Computers and Accessibility (ASSETS 2020)

  This paper presents a novel approach to mobile device interaction for people with severe motor impairments: using eyelid gestures detected by the smartphone's front-facing camera. While existing eye-based interaction research has primarily focused on gaze direction and simple…

  motor accessibility · mobile accessibility · input methods · gesture interaction · eye tracking

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