About this Event
Electrical Engineering and Computer Science (EECS)
Ph.D. Dissertation Defense
“Inclusive Text Entry Techniques for Mobile Devices”
Electrical Engineering and Computer Science
University of California, Merced
Text entry is ubiquitous – we enter text everywhere on various devices:
from composing emails on smartphones to replying to text messages directly from the wrist on smartwatches. Today, text entry is essential not only to get work done but also to keep in touch with our loved ones. A big chunk of these activities occurs on mobile devices, particularly tablet computers, smartphones, and smartwatches. These devices provide on-the-go interactions and have the potential to make users more independent and productive.
Although text entry is considered to be a standard feature on these devices, mobile text entry is still difficult due to a number of factors, such as reliance on precise target selection. Difficulties in mobile text entry are amplified for people with blindness and motor disabilities or those experiencing situational impairments. In this talk, I will discuss the pressing challenges in mobile text entry, then present solutions to these.
First, I will demonstrate a novel chorded keyboard that both sighted and people with vision impairments can use. Next, I will demonstrate a new gesture-based text entry method that facilitates skill transfer between multiple mobile devices. Then, I will present a novel method that enables people with limited dexterity to enter text on smartwatches with one finger.
Finally, I will present new action-level performance metrics that account for the error rate, accuracy, and complexity of multi-step chorded and constructive methods.
Gulnar Rakhmetulla is a Ph.D. candidate of EECS at UC Merced. Gulnar’s primary research interest lies in the design and development of accessible input techniques for everyone by making them more intuitive and effective.
Particularly, her research focuses on inclusive text entry techniques for mobile devices, such as smartphones and smartwatches. She has received one best paper award and multiple graduate fellowships. She has a Master of Science from the University of Sheffield, United Kingdom, and a Bachelor of Science from International Information Technology University, Almaty, Kazakhstan.
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