Texto completo
Vista Previa |
PDF (Portable Document Format)
- Se necesita un visor de ficheros PDF, como GSview, Xpdf o Adobe Acrobat Reader
Descargar (193kB) | Vista Previa |
Using a causal smoothing to improve the performance of an on-line neural network glucose prediction algorithm
Cita
Pérez Gandía, Carmen, Garcia Garcia, Fernando, García Sáez, Gema 
ORCID: https://orcid.org/0000-0002-8396-8185, Rodríguez Herrero, Agustín, Gómez Aguilera, Enrique Javier ORCID: https://orcid.org/0000-0001-6998-1407, Rigla Cros, Mercedes and Hernando Pérez, María Elena ORCID: https://orcid.org/0000-0001-6182-313X
(2012).
Using a causal smoothing to improve the performance of an on-line neural network glucose prediction algorithm.
En: "5th Conference on Advanced Technologies & Treatments for Diabetes, Barcelona, Spain, 2012", 08/02/2012 - 11/02/2012, BARCELONA. pp..
ORCID: https://orcid.org/0000-0002-8396-8185, Rodríguez Herrero, Agustín, Gómez Aguilera, Enrique Javier ORCID: https://orcid.org/0000-0001-6998-1407, Rigla Cros, Mercedes and Hernando Pérez, María Elena ORCID: https://orcid.org/0000-0001-6182-313X
(2012).
Using a causal smoothing to improve the performance of an on-line neural network glucose prediction algorithm.
En: "5th Conference on Advanced Technologies & Treatments for Diabetes, Barcelona, Spain, 2012", 08/02/2012 - 11/02/2012, BARCELONA. pp..
Descripción
| Título: | Using a causal smoothing to improve the performance of an on-line neural network glucose prediction algorithm |
|---|---|
| Autor/es: |
|
| Tipo de Documento: | Ponencia en Congreso o Jornada (Póster) |
| Título del Evento: | 5th Conference on Advanced Technologies & Treatments for Diabetes, Barcelona, Spain, 2012 |
| Fechas del Evento: | 08/02/2012 - 11/02/2012 |
| Lugar del Evento: | BARCELONA |
| Título del Libro: | Proceedings 5th Conference on Advanced Technologies & Treatments for Diabetes, Barcelona, Spain, 2012 |
| Fecha: | Febrero 2012 |
| Materias: | |
| ODS: | |
| Escuela: | E.T.S.I. Telecomunicación (UPM) |
| Departamento: | Tecnología Fotónica [hasta 2014] |
| Licencias Creative Commons: | Reconocimiento - Sin obra derivada - No comercial |
Resumen
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.
Más información
| ID de Registro: | 20391 |
|---|---|
| Identificador DC: | https://oa.upm.es/20391/ |
| Identificador OAI: | oai:oa.upm.es:20391 |
| Depositado por: | Memoria Investigacion |
| Depositado el: | 15 Oct 2013 16:37 |
| Ultima Modificación: | 04 Jul 2024 06:17 |
Acciones
- Estadísticas
- Exportar cita
- Editar (sólo personal del Archivo)
