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• Using data from social media websites to inspire the design of assistive technology

  Xing Yu · 2016 · Proceedings of the 13th International Web for All Conference (W4A)

  This doctoral consortium paper proposes using social media data as a low-cost, scalable method to inform the design of assistive technology, addressing limitations of traditional user research approaches. The author argues that designing assistive technology faces unique…

  assistive technology · social media · natural language processing · machine learning · prosthetics

• Computer vision-based analysis of web page structure for assistive interfaces

  Michael Cormier · 2016 · Proceedings of the 13th International Web for All Conference (W4A)

  This doctoral consortium paper proposes a novel approach to understanding web page structure by analyzing rendered page images using computer vision, rather than relying on the DOM tree or source code as most existing web page segmentation methods do. The author argues that the…

  computer vision · web page segmentation · screen reader accessibility · cognitive accessibility · machine learning

• Supporting the selection of web content modality based on user interactions logs

  Fabiano Marcon de Moraes, Vagner Figueredo de Santana, Juliana Cristina Braga · 2016 · Proceedings of the 13th International Web for All Conference (W4A)

  This paper explores using machine learning to automatically detect whether a web user is employing assistive technology based solely on their interaction patterns during a single pageview, without requiring explicit profile configuration or customization. Grounded in Universal…

  universal design · machine learning · personalization · assistive technology · user interaction

• Using Web Interaction to Monitor Parkinson's Disease Progression through Behavioural Inferences on the Web

  Julio Vega · 2016 · Proceedings of the 13th International Web for All Conference (W4A)

  This doctoral consortium paper from the University of Manchester proposes a novel approach to monitoring Parkinson's Disease (PD) progression using passive smartphone data collection and web interaction analysis, replacing the intrusive wearable devices and scripted evaluation…

  health monitoring · Parkinson's disease · smartphones · machine learning · digital health

• Laying a Foundation for the Graphical Course Map

  Linda DuHadway, Thomas C. Henderson · 2016 · Proceedings of the 13th International Web for All Conference (W4A)

  This paper from the University of Utah presents ENABLE, a system that transforms traditional linear, text-based learning management system (LMS) course presentations into interactive graphical course maps. The authors argue that current LMS platforms like Canvas impose two…

  education accessibility · personalized learning · data visualization · learning management systems · machine learning

• Supporting Orientation of People with Visual Impairment: Analysis of Large Scale Usage Data

  Hernisa Kacorri, Sergio Mascetti, Andrea Gerino, Dragan Ahmetovic, Hironobu Takagi, Chieko Asakawa · 2016 · Proceedings of the 18th International ACM SIGACCESS Conference on Computers and Accessibility (ASSETS '16)

  This paper analyzes large-scale remote usage data from iMove, an iOS GPS-based orientation app for people with visual impairments, to understand how users interact with assistive navigation technology in real-world conditions. Traditional assistive technology user studies are…

  visual impairment · blindness · navigation · orientation and mobility · mobile accessibility

• A Personalizable Mobile Sound Detector App Design for Deaf and Hard-of-Hearing Users

  Danielle Bragg, Nicholas Huynh, Richard E. Ladner · 2016 · Proceedings of the 18th International ACM SIGACCESS Conference on Computers and Accessibility (ASSETS '16)

  This paper presents the design and evaluation of a personalizable mobile phone app that detects sounds of interest to deaf and hard-of-hearing (DHH) users by learning from training examples recorded by the user themselves. Unlike existing commercial sound detection products —…

  deaf and hard of hearing · mobile accessibility · machine learning · sound detection · personalization

• Sign Transition Modeling and a Scalable Solution to Continuous Sign Language Recognition for Real-World Applications

  Kehuang Li, Zhengyu Zhou, Chin-Hui Lee · 2016 · ACM Transactions on Accessible Computing

  This paper presents a scalable framework for continuous sign language recognition (SLR) designed to work in real-world conditions using affordable hardware. The researchers address a fundamental challenge in SLR: modeling the transitions between signs. Unlike spoken language…

  sign language recognition · hidden Markov models · machine learning · deaf and hard of hearing · wearable technology

• Isolated Sign Language Recognition with Grassmann Covariance Matrices

  Hanjie Wang, Xiujuan Chai, Xiaopeng Hong, Guoying Zhao, Xilin Chen · 2016 · ACM Transactions on Accessible Computing

  This paper proposes a novel method for isolated sign language recognition using Grassmann Covariance Matrices (GCM) to fuse multimodal features captured by Microsoft Kinect. With 360 million people worldwide affected by hearing loss—21 million in China alone—automatic sign…

  sign language recognition · Chinese sign language · computer vision · machine learning · deaf and hard of hearing

9 results.