Observatorio de I+D+i UPM

Memorias de investigación
Research Publications in journals:
Classification of Stabilometric Time-Series Using an Adaptive Fuzzy Inference Neural Network System
Year:2010
Research Areas
  • Information technology and adata processing,
  • Computer systems
Information
Abstract
Stabilometry is a branch of medicine that studies balance-related human functions. The analysis of stabilometric-generated time series can be very useful to the diagnosis and treatment balance-related dysfunctions such as dizziness. In stabilometry, the key nuggets of information in a time series signal are concentrated within definite time periods known as events. In this study, a feature extraction scheme has been developed to identify and characterise the events. The proposed scheme utilises a statistical method that goes through the whole time series from the start to the end, looking for the conditions that define events, according to the experts¿ criteria. Based on these extracted features, an Adaptive Fuzzy Inference Neural Network (AFINN) has been applied for the classification of stabilometric signals. The experimental results validated the proposed methodology.
International
Si
JCR
No
Title
Lecture Notes in Artificial Intelligence
ISBN
0302-9743
Impact factor JCR
0
Impact info
Volume
6113
10.1007/978-3-642-13208-7_79
Journal number
From page
635
To page
642
Month
JUNIO
Ranking
Participants
  • Autor: Aurora Perez Perez (UPM)
  • Autor: Juan Alfonso Lara Torralbo (UPM)
  • Participante: Pari Jahankhani
  • Autor: Juan Pedro Caraca-Valente Hernandez (UPM)
  • Participante: Vassilis Kodogiannis
Research Group, Departaments and Institutes related
  • Creador: Grupo de Investigación: Grupo de Investigación en Tecnología Informática y de las Comunicaciones: CETTICO
S2i 2019 Observatorio de investigación @ UPM con la colaboración del Consejo Social UPM
Cofinanciación del MINECO en el marco del Programa INNCIDE 2011 (OTR-2011-0236)
Cofinanciación del MINECO en el marco del Programa INNPACTO (IPT-020000-2010-22)