Memorias de investigación
Ponencias en congresos:
Comparing Posturographic Time Series Through Events Detection
Año:2008
Áreas de investigación
  • Inteligencia artificial
Datos
Descripción
The comparison of two time series and the extraction of subsequences that are common to the two is a complex data mining problem. Many existing techniques, like the Discrete Fourier transform (DFT), offer solutions for comparing two whole time series. Often, however, the important thing is to analyse certain regions, known as events, rather than the whole times series. This applies to domains like the stock market, seismography or medicine. In this paper, we propose a technique for comparing two time series by analysing the events present in the two. The proposed technique is applied to time series generated by stabilometric and posturographic systems within a branch of medicine studying balance-related functions in human beings.
Internacional
Si
Nombre congreso
21st IEEE International Symposium on Computer-Based Medical Systems
Tipo de participación
960
Lugar del congreso
Jyvaskyla, Finlandia
Revisores
No
ISBN o ISSN
1063-7125
DOI
Fecha inicio congreso
17/06/2008
Fecha fin congreso
19/06/2008
Desde la página
293
Hasta la página
295
Título de las actas
Proceedings 21st IEEE International Symposium on Computer-Based Medical Systems
Esta actividad pertenece a memorias de investigación
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
  • Departamento: Lenguajes y Sistemas Informáticos e Ingeniería de Software