Memorias de investigación
Artículos en revistas:
Classification of Stabilometric Time-Series Using an Adaptive Fuzzy Inference Neural Network System
Año:2010
Áreas de investigación
  • Ciencias de la computación y tecnología informática,
  • Informática
Datos
Descripción
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.
Internacional
Si
JCR del ISI
No
Título de la revista
Lecture Notes in Artificial Intelligence
ISSN
0302-9743
Factor de impacto JCR
0
Información de impacto
Volumen
6113
DOI
10.1007/978-3-642-13208-7_79
Número de revista
Desde la página
635
Hasta la página
642
Mes
JUNIO
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Participantes
Grupos de investigación, Departamentos, Centros e Institutos de I+D+i relacionados
  • Creador: Grupo de Investigación: Grupo de Investigación en Tecnología Informática y de las Comunicaciones: CETTICO