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Memorias de investigación
Communications at congresses:
Comparing Posturographic Time Series Through Events Detection
Year:2008
Research Areas
  • Artificial intelligence
Information
Abstract
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.
International
Si
Congress
21st IEEE International Symposium on Computer-Based Medical Systems
960
Place
Jyvaskyla, Finlandia
Reviewers
No
ISBN/ISSN
1063-7125
Start Date
17/06/2008
End Date
19/06/2008
From page
293
To page
295
Proceedings 21st IEEE International Symposium on Computer-Based Medical Systems
Participants
  • Participante: AFRICA LÓPEZ-ILLESCAS (Consejo Superior de Deportes)
  • Participante: GUILLERMO MORENO (Consejo Superior de Deportes)
  • Autor: Aurora Perez Perez (UPM)
  • Participante: JUAN ALFONSO LARA TORRALBA (UPM)
  • Autor: Juan Pedro Caraca-Valente Hernandez (UPM)
Research Group, Departaments and Institutes related
  • Creador: Grupo de Investigación: Grupo de Investigación en Tecnología Informática y de las Comunicaciones: CETTICO
  • Departamento: Lenguajes y Sistemas Informáticos e Ingeniería de Software
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