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Modeling an Automatic Adjustment of Scanning Rate Using Fuzzy Inference Logic

Ka, Hyun and Simpson, Richard (2011) Modeling an Automatic Adjustment of Scanning Rate Using Fuzzy Inference Logic. In: the Annual Conference on Rehabilitation Engineering, June 2011 - June 2011, Toronto, ON.

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Abstract

Single-switch scanning is one of the slowest way for people with severe motor impairments to access a wide range of assistive technologies, such as entering text into computer applications, manipulating alternative and augmentative communication devices, and operating power wheelchairs. Automating scanning rate adjustment has been investigated as a means of improving selection rate by several research groups [1-6], using probabilistic methods such as uncertainty factors and Bayesian networks. In practice, however, when assessing and documenting their client’s needs, clinicians tend to prefer specifying linguistic values, such as slow, medium, and fast, rather than numerical values. In this respect, fuzzy logic can be an alternative to the existing approaches because it can capture the meaning of linguistic variables whose values are words rather than numbers [7, 8]. This paper describes our approach to modeling the automatic adjustment of scan rate using fuzzy logic.


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Details

Item Type: Conference or Workshop Item (Paper)
Status: Published
Creators/Authors:
CreatorsEmailPitt UsernameORCID
Ka, Hyunhyk21@pitt.eduHYK21
Simpson, Richard
Date: June 2011
Date Type: Publication
Access Restriction: No restriction; Release the ETD for access worldwide immediately.
Journal or Publication Title: Proceedings of the Annual Conference on Rehabilitation Engineering
Publisher: RESNA
Event Title: the Annual Conference on Rehabilitation Engineering
Event Dates: June 2011 - June 2011
Event Type: Conference
Institution: University of Pittsburgh
Schools and Programs: School of Health and Rehabilitation Sciences > Sports Medicine and Nutrition
Refereed: Yes
Date Deposited: 22 Sep 2014 19:48
Last Modified: 25 Aug 2017 05:01
URI: http://d-scholarship.pitt.edu/id/eprint/22870

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