Accessible Gesture Typing on Smartphones for People with Low Vision

While gesture typing is widely adopted on touchscreen keyboards, its support for low vision users is limited. We have designed and implemented two keyboard prototypes, layout-magnified and key-magnified keyboards, to enable gesture typing for people with low vision. Both keyboards facilitate uninterrupted access to all keys while the screen magnifier is active, allowing people with low vision to input text with one continuous stroke. Furthermore, we have created a kinematics-based decoding algorithm to accommodate the typing behavior of people with low vision. This algorithm can decode the gesture input even if the gesture trace deviates from a pre-defined word template, and the starting position of the gesture is far from the starting letter of the target word. Our user study showed that the key-magnified keyboard achieved 5.28 words per minute, 27.5% faster than a conventional gesture typing keyboard with voice feedback.

Authors

Institutions

Publication Details

Published
2024-10-11
DOI
https://doi.org/10.1145/3654777.3676447
Citations
3
Primary Topic
Tactile and Sensory Interactions
Type
article
Field-Weighted Citation Impact
1.03

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Accessible Gesture Typing on Smartphones for People with Low Vision

I. V. Ramakrishnan, Xiaojun Bi, Vikas Ashok, William Seiple et al.
3 citations
Tactile and Sensory Interactions
1.03
article

Accessible Gesture Typing on Smartphones for People with Low Vision

I. V. Ramakrishnan, Xiaojun Bi, Vikas Ashok, William Seiple, Dan Zhang, Zhi Li
article en
3 citations

Abstract

While gesture typing is widely adopted on touchscreen keyboards, its support for low vision users is limited. We have designed and implemented two keyboard prototypes, layout-magnified and key-magnified keyboards, to enable gesture typing for people with low vision. Both keyboards facilitate uninterrupted access to all keys while the screen magnifier is active, allowing people with low vision to input text with one continuous stroke. Furthermore, we have created a kinematics-based decoding algorithm to accommodate the typing behavior of people with low vision. This algorithm can decode the gesture input even if the gesture trace deviates from a pre-defined word template, and the starting position of the gesture is far from the starting letter of the target word. Our user study showed that the key-magnified keyboard achieved 5.28 words per minute, 27.5% faster than a conventional gesture typing keyboard with voice feedback.

Vol. 2024
New York University (US), Stony Brook University (US), Old Dominion University (US)
National Science Foundation, National Institutes of Health
Openalex Percentile: Top 24%
Tactile and Sensory Interactions
1.03
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.