Campus Units

Mechanical Engineering

Document Type

Article

Publication Version

Accepted Manuscript

Publication Date

9-2018

Journal or Book Title

Biotribology

Volume

15

First Page

1

Last Page

8

DOI

10.1016/j.biotri.2018.07.001

Abstract

The ability to discriminate among various tactual elements is crucial to any tactile communication system, such as in assistive technology for those with visual impairment. In previous work, the authors investigated the ability to differentiate textures having a large surface area. In the current work, the objective was to determine how diminishing surface area affects perception, and the extent to which limited area inhibits with the friction-based perception. A perception study in combination with friction measurement was performed to address this issue. Circular texture samples consisting of abrasive papers of P800, P1200 and P2500 grit, respectively, of three different sizes, 38.1 mm, 9.5 mm and 3.2 mm, were used as stimuli. Same size samples were presented in pairwise combinations to determine the mean probabilities of differentiation for an abrasive paper pair at different sizes. Results from the perception measurement indicated that decreasing size of the texture sample resulted in a decrease in the ability to both reliably differentiate different-grit abrasive pairs and reliably identify same-grit abrasive pairs. Finger friction measurements from the participants suggested a possible edge effect on the friction of the samples. Silicone-based probes were also employed for friction measurement of the texture samples to identify friction mechanisms as well as confirm the magnitude of the effect of sample edges on total friction.

Comments

This is a manuscript of an article published as Chimata, G. P., and C. J. Schwartz. "Investigation of the role of diminishing surface area on friction-based tactile discrimination of textures." Biotribology 15 (2018): 1-8. DOI: 10.1016/j.biotri.2018.07.001. Posted with permission.

Creative Commons License

Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.

Copyright Owner

Elsevier Ltd.

Language

en

File Format

application/pdf

Available for download on Friday, July 24, 2020

Published Version

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