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; Zárate Banda, Magdalena; Barron Adame, Jose Miguel; Martínez Celorio, René Alfredo y 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. En: "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.

Descripción

Título: Design Of the Approximation Function of a Pedometer based on Artificial Neural Network for the Healthy Life Style Promotion in Diabetic Patients
Autor/es:
  • Vega Corona, Antonio
  • Zárate Banda, Magdalena
  • Barron Adame, Jose Miguel
  • Martínez Celorio, René Alfredo
  • Andina de la Fuente, Diego
Tipo de Documento: Ponencia en Congreso o Jornada (Artículo)
Título del Evento: Seventh Mexican International Conference on Artificial Intelligence MICAI '08.
Fechas del Evento: 27/10/2008-31/10/2008
Lugar del Evento: Atizapán de Zaragoza, Mexico
Título del Libro: Proceedings of the special session of the Seventh Mexican International Conference on Artificial Intelligence
Fecha: 2008
ISBN: 978-0-7695-3441-1
Materias:
Palabras Clave Informales: Artificial neural networks, pedometer, approximation function, diabetes mellitus, healthy life style.
Escuela: E.T.S.I. Telecomunicación (UPM)
Departamento: Señales, Sistemas y Radiocomunicaciones
Licencias Creative Commons: Reconocimiento - Sin obra derivada - No comercial

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Localizaciones alternativas

URL Oficial: http://callix.azc.uam.mx/micai2008/

Resumen

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.

Más información

ID de Registro: 3698
Identificador DC: http://oa.upm.es/3698/
Identificador OAI: oai:oa.upm.es:3698
Depositado por: Memoria Investigacion
Depositado el: 12 Jul 2010 10:00
Ultima Modificación: 20 Abr 2016 13:11
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