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Some individuals with motor impairments communicate using a single switch - such as a button click, air puff, or blink. Row-column scanning provides a method for choosing items arranged in a grid using a single switch. An alternative, Nomon, allows potential selections to be arranged arbitrarily rather than requiring a grid (as desired for gaming, drawing, etc.) - and provides an alternative probabilistic selection method. While past results suggest that Nomon may be faster and easier to use than row-column scanning, no work has yet quantified performance of the two methods over longer time periods or in tasks beyond writing. In this paper, we also develop and validate a webcam-based switch that allows a user without a motor impairment to approximate the response times of a motor-impaired single switch user; although the approximation is not a replacement for testing with single-switch users, it allows us to better initialize, calibrate, and evaluate our method. Over 10 sessions with the webcam switch, we found users typed faster and more easily with Nomon than with row-column scanning. The benefits of Nomon were even more pronounced in a picture-selection task. Evaluation and feedback from a motor-impaired switch user further supports the promise of Nomon.
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Demonstrating Nomon: A Flexible Interface for Noisy Single-Switch Users
Some individuals with motor impairments communicate using a single switch - such as a button click, air puff, or blink. Our software, Nomon, provides a method for single-switch users to select between items on a screen. Nomon’s flexibility stems from its probabilistic selection method, which allows potential options to be arranged arbitrarily rather than requiring they be arranged in a grid. As a result, Nomon can be used for a host of applications - including gaming, drawing, and web browsing. Focusing on accessibility, we updated the Nomon interface in collaboration with a switch user and with experts in Augmentative and Alternative Communication (AAC). We present our updated Nomon interface as an open-source web application.
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- Award ID(s):
- 1750193
- PAR ID:
- 10325858
- Date Published:
- Journal Name:
- CHI '22: CHI Conference on Human Factors in Computing Systems (extended abstracts)
- Page Range / eLocation ID:
- 1 to 4
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.1145/3491101.3519892
