Using a causal smoothing to improve the performance of an on-line neural network glucose prediction algorithm

Pérez Gandía, Carmen and Garcia Garcia, Fernando and García Sáez, Gema and Rodriguez Herrero, Agustin and Gómez Aguilera, Enrique J. and Rigla Cros, Mercedes and Hernando Pérez, María Elena (2012). Using a causal smoothing to improve the performance of an on-line neural network glucose prediction algorithm. In: "5th Conference on Advanced Technologies & Treatments for Diabetes, Barcelona, Spain, 2012", 08/02/2012 - 11/02/2012, BARCELONA. pp..

Description

Title: Using a causal smoothing to improve the performance of an on-line neural network glucose prediction algorithm
Author/s:
  • Pérez Gandía, Carmen
  • Garcia Garcia, Fernando
  • García Sáez, Gema
  • Rodriguez Herrero, Agustin
  • Gómez Aguilera, Enrique J.
  • Rigla Cros, Mercedes
  • Hernando Pérez, María Elena
Item Type: Presentation at Congress or Conference (Poster)
Event Title: 5th Conference on Advanced Technologies & Treatments for Diabetes, Barcelona, Spain, 2012
Event Dates: 08/02/2012 - 11/02/2012
Event Location: BARCELONA
Title of Book: Proceedings 5th Conference on Advanced Technologies & Treatments for Diabetes, Barcelona, Spain, 2012
Date: February 2012
Subjects:
Faculty: E.T.S.I. Telecomunicación (UPM)
Department: Tecnología Fotónica [hasta 2014]
Creative Commons Licenses: Recognition - No derivative works - Non commercial

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Abstract

This work evaluates a spline-based smoothing method applied to the output of a glucose predictor. Methods:Our on-line prediction algorithm is based on a neural network model (NNM). We trained/validated the NNM with a prediction horizon of 30 minutes using 39/54 profiles of patients monitored with the Guardian® Real-Time continuous glucose monitoring system The NNM output is smoothed by fitting a causal cubic spline. The assessment parameters are the error (RMSE), mean delay (MD) and the high-frequency noise (HFCrms). The HFCrms is the root-mean-square values of the high-frequency components isolated with a zero-delay non-causal filter. HFCrms is 2.90±1.37 (mg/dl) for the original profiles.

More information

Item ID: 20391
DC Identifier: http://oa.upm.es/20391/
OAI Identifier: oai:oa.upm.es:20391
Deposited by: Memoria Investigacion
Deposited on: 15 Oct 2013 16:37
Last Modified: 21 Apr 2016 23:09
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