Making Technologies Accessible for All
The TRACE RERC is a research and development center at the University of Maryland, College Park. It is part of the College of Information and is funded by NIDILRR (the National Institute on Disability, Independent Living, and Rehabilitation Research).
Our Mission
Our mission at the Trace Research and Development Center is to capitalize on the potential that technologies hold for people experiencing barriers due to disability, aging, or digital literacy, and to prevent emerging technologies from creating new barriers for these individuals. In doing this, we bring together disciplines such as information science, computer science, engineering, disability studies, law, and public policy. We engage in research, development, tech transfer, education, policy, and advocacy.
Our vision is a world that is accessible and usable by people of all ages and all abilities – each experiencing information and technologies in a way that they can understand and use.
What is TRACE Working on Right Now?
AI and Accessibility
Existing AI technologies are increasing in number faster than assistive technologies, which leaves some people with disabilities behind. How can we incorporate individuals with disabilities when forming datasets? Check out our work on 3D motion capture datasets of Blind individuals for training AI.
Technology and Older Adults
Our technology-focused society often leaves out people who are unable to learn skills such as opening a browser, emailing, etc. How do older adults feel about technology and the constant changes that are being made?
Accessible Kiosks
With a rise in touchscreen-based kiosks in public places, recreation of accessible kiosks is necessary, especially for individuals who need assistive technologies, such as screen readers, to read content. How can kiosks be designed to incorporate features for blind and low-vision users?
Technologies Developed By TRACE
Morphic
Morphic is an application that makes computers more accessible by providing accessibility and usability features (such as large text or color contrast) that can be used on any computer or device that has Morphic installed.
PEAT
Photosensitive Epilepsy is a condition in which a person is susceptible to seizures when exposed to content (such as videos, movies, and games) with specific features, like flashing lights or visual patterns. PEAT, or Photosensitive Epilepsy Analysis Tool, is a software program that can be used to scan content for sensitive material to help creators release content that can be enjoyed by all.
EZ Access
EZ Access is a set of interface enhancements that can make transaction machines and kiosks more accessible to people with disabilities, especially those who are Blind or Low Vision. It involves a tactile keypad with raised buttons that users can feel and press.
Learn About Our History
The Trace R&D Center was formed in 1971 by Gregg Vanderheiden. Since then, it has developed numerous technologies and tools that help people with varying abilities.
News
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TRACE is Attending CSUN
CSUN, California State University, Northridge, hosts an assistive technology conference every year. This conference is one of the biggest accessibility conferences in the world, and is sponsored by various well-known companies like Amazon, CVS Health, Google, Microsoft, and Walmart. Dr. Bern Jordan will be presenting his work on accessible kiosks in a session… Continue Reading TRACE is Attending CSUN
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TRACE Attended the National Federation of the Blind State Convention
On February 14th, 2025, TRACE attended the NFB State Convention in Ocean City, Maryland. Dr. Bern Jordan designed and developed a prototype for accessible kiosks which he showcased during this convention. Kiosks are becoming more and more popular: we order food with them, check bags at the airport with them, and more. However, these kiosks… Continue Reading TRACE Attended the National Federation of the Blind State Convention
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Capturing Blind People’s Movements to Improve Safety
Autonomous vehicles are trained on datasets to detect human movement in order to prevent collisions. However, these datasets often only include the movements of sighted individuals. Blind people often use canes to feel around for curbs and bumps, and these movements may not be interpreted properly by current autonomous vehicles, leading to potential life-threatening situations… Continue Reading Capturing Blind People’s Movements to Improve Safety
