Design Of the Approximation Function of a Pedometer based on Artificial Neural Network for the Healthy Life Style Promotion in Diabetic Patients

Vega Corona, Antonio and Zárate Banda, Magdalena and Barron Adame, Jose Miguel and Martínez Celorio, René Alfredo and Andina de la Fuente, Diego (2008). Design Of the Approximation Function of a Pedometer based on Artificial Neural Network for the Healthy Life Style Promotion in Diabetic Patients. In: "Seventh Mexican International Conference on Artificial Intelligence MICAI '08.", 27/10/2008-31/10/2008, Atizapán de Zaragoza, Mexico. ISBN 978-0-7695-3441-1. pp. 325-329. https://doi.org/10.1109/MICAI.2008.24.

Description

Title: Design Of the Approximation Function of a Pedometer based on Artificial Neural Network for the Healthy Life Style Promotion in Diabetic Patients
Author/s:
  • Vega Corona, Antonio
  • Zárate Banda, Magdalena
  • Barron Adame, Jose Miguel
  • Martínez Celorio, René Alfredo
  • Andina de la Fuente, Diego
Item Type: Presentation at Congress or Conference (Article)
Event Title: Seventh Mexican International Conference on Artificial Intelligence MICAI '08.
Event Dates: 27/10/2008-31/10/2008
Event Location: Atizapán de Zaragoza, Mexico
Title of Book: Proceedings of the special session of the Seventh Mexican International Conference on Artificial Intelligence
Date: 2008
ISBN: 978-0-7695-3441-1
Subjects:
Freetext Keywords: Artificial neural networks, pedometer, approximation function, diabetes mellitus, healthy life style.
Faculty: E.T.S.I. Telecomunicación (UPM)
Department: Señales, Sistemas y Radiocomunicaciones
Creative Commons Licenses: Recognition - No derivative works - Non commercial

Full text

[img]
Preview
PDF - Requires a PDF viewer, such as GSview, Xpdf or Adobe Acrobat Reader
Download (208kB) | Preview

Abstract

The present study describes the design of an Artificial Neural Network to synthesize the Approximation Function of a Pedometer for the Healthy Life Style Promotion. Experimentally, the approximation function is synthesized using three basic digital pedometers of low cost, these pedometers were calibrated with an advanced pedometer that calculates calories consumed and computes distance travelled with personal stride input. The synthesized approximation function by means of the designed neural network will allow to reply the calibration experiment for multiple patients with Diabetes Mellitus in Healthy Life Style promotion programs. Artificial Neural Networks have been developed for a wide variety of computational problems in cognition, pattern recognition, and decision making. The Healthy Life Style refer to adequate nutrient ingest, physical activity, time to rest, stress control, and a high self-esteem. The pedometer is a technological device that helps to control the physical activity in the diabetic patient. A brief description of the Artificial Neural Network designed to synthesize the Approximation Function, the obtained Artificial Neural Network structure and results in the Approximation Function synthesis for three patients are presented. The advantages and disadvantages of the method are discussed and our conclusions are presented.

More information

Item ID: 3698
DC Identifier: http://oa.upm.es/3698/
OAI Identifier: oai:oa.upm.es:3698
DOI: 10.1109/MICAI.2008.24
Official URL: http://callix.azc.uam.mx/micai2008/
Deposited by: Memoria Investigacion
Deposited on: 12 Jul 2010 10:00
Last Modified: 20 Apr 2016 13:11
  • Logo InvestigaM (UPM)
  • Logo GEOUP4
  • Logo Open Access
  • Open Access
  • Logo Sherpa/Romeo
    Check whether the anglo-saxon journal in which you have published an article allows you to also publish it under open access.
  • Logo Dulcinea
    Check whether the spanish journal in which you have published an article allows you to also publish it under open access.
  • Logo de Recolecta
  • Logo del Observatorio I+D+i UPM
  • Logo de OpenCourseWare UPM