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Use of unsupervised neural networks for classification of blood pressure time series

  • María José Rodríguez
  • Francisco del Pozo
  • María Teresa Arredondo
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 686)

Abstract

This paper describes a method to classify blood pressure time profiles using artificial neural network with unsupervised learning. Kohonen's Topology Preserving Maps were used to identify similar characteristics in 100 profiles from different subjects. Afterwards, obtained results were validated using another group of 142 blood pressure profiles.

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References

  1. [1]
    J.L. Palma: “Control ambulatorio continuo de la presión arterial”. In: Avances en Electrocardiología. A. Bayés de Luna Ed. Barcelona: Doyma 1981, 177–182.Google Scholar
  2. [2]
    T. Kohonen: “The Self-Organizing Map”, Proceedings of the IEEE 1990; 78: 1464–1480.Google Scholar
  3. [3]
    R.P. Lippmann: “An Introduction to Computing with Neural Nets”, IEEE ASSP Magazine; April 1987: 4–22.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1993

Authors and Affiliations

  • María José Rodríguez
    • 1
  • Francisco del Pozo
    • 1
  • María Teresa Arredondo
    • 1
  1. 1.Dep. de TE y Bioingeniería, ETSI de TelecomunicaciónUniv. Politécnica de MadridEspaña

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