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Nutritional assessment of children under five based on anthropometric measurements with image processing techniques

  • Victor A. Ayma
  • , Victor H. Ayma
  • , Armando Torre
  • , Lizette Ganoza

Research output: Chapter in Book/Report/Conference proceedingPaper (Conference contribution)peer-review

Abstract

Nutritional assessment is an important evaluation to prevent and control malnutrition, which is one of the main causes associated with child mortality. Weight and height are the most frequently measured morphological traits which in combination with child's gender and age, generates anthropometric indices to establish child's nutritional status. Nevertheless, accomplishment of this task in rural areas is difficult because of complications to transport bulky and heavy equipment, which must be properly and adequately calibrated. This work proposed a novel approach to perform nutritional assessments of children under five, through a system focused on the estimation of anthropometric indices, based on the measurements obtained from a set of body part images and its relations with child's gender and age. The results showed that sensitivity and specificity for the anthropometric indicators, ranged from 66% to 100% and 88% to 100%, respectively. Moreover, overall accuracies were over 85% up to 100%. Additionally, the experiments conducted shown our method as a viable solution to perform nutritional evaluations via accurate anthropometric index estimations.

Original languageEnglish
Title of host publicationProceedings of the 2016 IEEE ANDESCON, ANDESCON 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781509025312
DOIs
StatePublished - 27 Jan 2017
Externally publishedYes
Event2016 IEEE ANDESCON, ANDESCON 2016 - Arequipa, Peru
Duration: 19 Oct 201621 Oct 2016

Publication series

NameProceedings of the 2016 IEEE ANDESCON, ANDESCON 2016

Conference

Conference2016 IEEE ANDESCON, ANDESCON 2016
Country/TerritoryPeru
CityArequipa
Period19/10/1621/10/16

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 2 - Zero Hunger
    SDG 2 Zero Hunger
  2. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Keywords

  • image processing
  • machine learning
  • malnutrition
  • neural networks
  • nutrition assessment

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