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Authors: Felipe Mancini ; Ivan Torres Pisa ; Liu Chiao Yi and Shirley Shizue Nagata Pignatari

Affiliation: Federal University of São Paulol, Brazil

Keyword(s): Artificial neural networks, posture, mouth breathing, clinical decision support systems.

Related Ontology Subjects/Areas/Topics: Biomedical Engineering ; Decision Support Systems ; Health Information Systems

Abstract: A number of factors can lead to changes in body posture, basically determined by alterations in the natural curvature of the spine. Such changes, in turn, may also result in secondary health problems. Mouth breathing is thought to be one of these problems. Experiments with healthy nasal breathing individuals have showed that when they are forced to breathe through their mouth only the natural shape of their spine curves change. However the characterization of the spine curvature in mouth breathers has not been done yet and the matter lies on the personal experience of the health professional. This study reports on the preliminary findings of a broader research which attempts to characterize the changes in the behaviour of the spine, caused by mouth breathing, by using artificial neural network modelling and data from 52 subjects. Four different models – backprogation, learning vector quantization (LVQ), and self-organizing map (SOM) – were tested for best performances in sensitivity and specificity in diagnosing mouth and nasal breathing children. Competitive-learning-based algorithms – LVQ and SOM – presented the best performance for current data set. (More)

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Paper citation in several formats:
Mancini, F.; Torres Pisa, I.; Chiao Yi, L. and Shizue Nagata Pignatari, S. (2008). SELECTION OF AN ARTIFICIAL NEURAL NETWORK MODEL TO DIAGNOSIS MOUTH-BREATHING CHILDREN. In Proceedings of the First International Conference on Health Informatics (BIOSTEC 2008) - Volume 2: HEALTHINF; ISBN 978-989-8111-16-6; ISSN 2184-4305, SciTePress, pages 197-200. DOI: 10.5220/0001042401970200

@conference{healthinf08,
author={Felipe Mancini. and Ivan {Torres Pisa}. and Liu {Chiao Yi}. and Shirley {Shizue Nagata Pignatari}.},
title={SELECTION OF AN ARTIFICIAL NEURAL NETWORK MODEL TO DIAGNOSIS MOUTH-BREATHING CHILDREN},
booktitle={Proceedings of the First International Conference on Health Informatics (BIOSTEC 2008) - Volume 2: HEALTHINF},
year={2008},
pages={197-200},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001042401970200},
isbn={978-989-8111-16-6},
issn={2184-4305},
}

TY - CONF

JO - Proceedings of the First International Conference on Health Informatics (BIOSTEC 2008) - Volume 2: HEALTHINF
TI - SELECTION OF AN ARTIFICIAL NEURAL NETWORK MODEL TO DIAGNOSIS MOUTH-BREATHING CHILDREN
SN - 978-989-8111-16-6
IS - 2184-4305
AU - Mancini, F.
AU - Torres Pisa, I.
AU - Chiao Yi, L.
AU - Shizue Nagata Pignatari, S.
PY - 2008
SP - 197
EP - 200
DO - 10.5220/0001042401970200
PB - SciTePress