Memorias de investigación
Ponencias en congresos:
Design Of The Approximation Function of a Pedometer based on Artificial Neural Network for the Healthy Life Style Promotion in Diabetic Patients
Año:2008
Áreas de investigación
  • Procesado y análisis de la señal
Datos
Descripción
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.
Internacional
Si
Nombre congreso
MICAI '08. Seventh Mexican International Conference on Artificial Intelligence
Tipo de participación
960
Lugar del congreso
Mexico City, Mexico
Revisores
Si
ISBN o ISSN
978-0-7695-3441-1/08
DOI
10.1109/MICAI.2008.24
Fecha inicio congreso
27/10/2008
Fecha fin congreso
31/10/2008
Desde la página
325
Hasta la página
329
Título de las actas
Lecture Notes in omputer Science - Lecture notes in Artificial Intelligence
Esta actividad pertenece a memorias de investigación
Participantes
  • Autor: A Vega-.Corona Universidad de Guanajuato, Méjico
  • Autor: M Zárate-Banda Universidad de Guanajuato, Méjico
  • Autor: Jose Miguel Barron Adame UPM
  • Autor: RA Martínez-Celorio Universidad de Guanajuato, Méjico
  • Autor: Diego Andina De la Fuente UPM
Grupos de investigación, Departamentos, Centros e Institutos de I+D+i relacionados
  • Creador: Grupo de Investigación: Grupo de Automatización en Señal y Comunicaciones (GASC)
  • Departamento: Señales, Sistemas y Radiocomunicaciones