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THE USE OF ORANGE CANVAS PROGRAM TO ANALYZE THE PERFORMANCE OF CHILDREN WITH CONGENITAL BLINDNESS IN THE PLANNED CODES SUBTEST ADAPTED

Topics: Cognitive Informatics; Data Visualization; Development of Assistive Technology; Human-Machine Interfaces for Disabled Persons; Pattern Recognition and Machine Learning

Authors: Felipe Pulcherio 1 ; Carla Verônica M. Marques 2 ; Carlo Oliveira E. S. de Oliveira 2 ; Maria M. D. Poyares 1 ; Eloisa Saboya 1 and Lidiane F. Silva 3

Affiliations: 1 Instituto Benjamin Constant, Brazil ; 2 UFRJ and NCE -UFRJ, Brazil ; 3 NCE – UFRJ, Brazil

Keyword(s): Orange canvas, Planned codes, Congenital blindness, Neuropsychological assessment.

Related Ontology Subjects/Areas/Topics: Biomedical Engineering ; Cognitive Informatics ; Data Engineering ; Data Management and Quality ; Data Manipulation ; Data Visualization ; Development of Assistive Technology ; Health Information Systems ; Human-Machine Interfaces for Disabled Persons ; Pattern Recognition and Machine Learning ; Sensor Networks

Abstract: At Laboratory of Cognitive Neuropsychology of the Benjamin Constant Institute (NEUROLAB-IBC) was realized a study aiming at exploiting the cognitive component and a possible clinical guidelines of children with congenital blindness from the adaptation of Planned Codes subtest of Das and Naglieri and the use of artificial intelligence laboratory Orange Canvas of the University of Ljubljana. Due to the scarcity of neuropsychological tests that assess brain function in congenital blind children in Brazil, Planned Codes provided satisfactory scenery and needed to adapt to the reality of the applicator and children, containing, therefore, features tactile, visual and translated into Portuguese. Moreover, the high-tech offered by Orange Canvas program, favored the possibility of completely automating the entire subtest. The sample consisted of 59 congenital blind children which are students of Specialized School, where 32 realized the whole subtest being 2 of 7 years old and 28 from 8 to 1 2 years old. To validate this study, was made a clustering of data inherent to the subtest with predictions drawn from behavioral analysis of children, through the Orange Canvas, where it was confirmed the effectiveness of that procedure in clustering the data associated with the predictions suggested. From the children performance, opens itself an intervention and creation field of neuropedagogical strategies computerized to improve the cognitive processing of congenital blind children. (More)

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Paper citation in several formats:
Pulcherio, F.; M. Marques, C.; Oliveira E. S. de Oliveira, C.; Poyares, M.; Saboya, E. and Silva, L. (2011). THE USE OF ORANGE CANVAS PROGRAM TO ANALYZE THE PERFORMANCE OF CHILDREN WITH CONGENITAL BLINDNESS IN THE PLANNED CODES SUBTEST ADAPTED . In Proceedings of the International Conference on Health Informatics (BIOSTEC 2011) - HEALTHINF; ISBN 978-989-8425-34-8; ISSN 2184-4305, SciTePress, pages 486-492. DOI: 10.5220/0003128604860492

@conference{healthinf11,
author={Felipe Pulcherio. and Carla Verônica {M. Marques}. and Carlo {Oliveira E. S. de Oliveira}. and Maria M. D. Poyares. and Eloisa Saboya. and Lidiane F. Silva.},
title={THE USE OF ORANGE CANVAS PROGRAM TO ANALYZE THE PERFORMANCE OF CHILDREN WITH CONGENITAL BLINDNESS IN THE PLANNED CODES SUBTEST ADAPTED },
booktitle={Proceedings of the International Conference on Health Informatics (BIOSTEC 2011) - HEALTHINF},
year={2011},
pages={486-492},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003128604860492},
isbn={978-989-8425-34-8},
issn={2184-4305},
}

TY - CONF

JO - Proceedings of the International Conference on Health Informatics (BIOSTEC 2011) - HEALTHINF
TI - THE USE OF ORANGE CANVAS PROGRAM TO ANALYZE THE PERFORMANCE OF CHILDREN WITH CONGENITAL BLINDNESS IN THE PLANNED CODES SUBTEST ADAPTED
SN - 978-989-8425-34-8
IS - 2184-4305
AU - Pulcherio, F.
AU - M. Marques, C.
AU - Oliveira E. S. de Oliveira, C.
AU - Poyares, M.
AU - Saboya, E.
AU - Silva, L.
PY - 2011
SP - 486
EP - 492
DO - 10.5220/0003128604860492
PB - SciTePress