Date of Award


Document Type


Degree Name

Master of Science in Electrical Engineering


Electrical & Computer Engineering and Computer Science

First Advisor

Christopher Martinez, Ph.D.


The development of accessible video games has been discussed through multiple publications in the 21st century; however, little to no attention has been given to non-electronic gaming. Like video games, Collectible Card Games (CCG) have also gained massive popularity, but no accessible guidelines have been created to help the disabled better play them. The need for inclusion in gaming is critical because it can act as a medium for social interaction and a learning tool for teaching. Today offers numerous technologies that can help those with disabilities, such as microcomputers, Artificial Intelligence (AI), Optical Character Recognition (OCR), and Text to Speech, can all be used to help those with disabilities. In this thesis, we create a proof of concept Accessible Technology to help those with low vision play CGG and show that guidelines that worked for video games can be brought over to help with CCG. We use a Raspberry Pi 4B and the Raspberry Pi HQ camera module, Scene Text Detection, OCR, and Text to Speech to read the cards of a CCG. This AT acts similar to a microscope where it captures the image of a card, finds the card’s name, feeds it to a database query, and reads the record from the database to the player. We performed several evaluations where the participant played a game of Yugioh, followed by answering a questionnaire. We found in these evaluations that the AT was primarily successful, and the user problems come from poor text to speech and participants having a hard time remembering or comprehending card information.


Assistive computer technology, Video games, Collectible card games