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Computational system for alternative and augmented communication for people with cerebral palsy

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Published:02 April 2014Publication History

ABSTRACT

Computational efforts for Alternative and Augmented Communication (AAC) must deal with two important issues, that slow down their spread: (1) the need for specific hardware and software in order to engage each different disability and (2) the different communication languages. This paper presents the PickNClick, a hardware/software apparatus that allows for ample AAC in Brazil. The PickNClick consists of a word and sentence prediction tool for Portuguese language to help people with cerebral palsy, in particular, spastic quadriplegic children. Experiments conducted presented good values concerning KSR metric and showed the software applicability cerebral palsy and spastic quadriplegic volunteer.

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  1. Computational system for alternative and augmented communication for people with cerebral palsy

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        • Published in

          cover image ACM Conferences
          EATIS '14: Proceedings of the 7th Euro American Conference on Telematics and Information Systems
          April 2014
          174 pages
          ISBN:9781450324359
          DOI:10.1145/2590651
          • Co-chair:
          • Claudio Cubillos,
          • General Chair:
          • Cristian Rusu,
          • Program Chair:
          • Dorian Gorgan

          Copyright © 2014 Owner/Author

          Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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          Association for Computing Machinery

          New York, NY, United States

          Publication History

          • Published: 2 April 2014

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          EATIS '14 Paper Acceptance Rate17of64submissions,27%Overall Acceptance Rate17of64submissions,27%
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