A competitive-based method for determining the number of groups: a clinical application

  • Authors:

  • Antonio Sánchez;Francisco Vico;Santiago Cabello;Francisco Veredas;Yamina Seamari;Isaac López;Javier Farfán;Guillermo García-Herrera

  • Affiliations:

  • Dept. Lenguajes y Ciencias de la Computación, ETSII Informática, Universidad de Málaga, Málaga, Spain;Dept. Lenguajes y Ciencias de la Computación, ETSII Informática, Universidad de Málaga, Málaga, Spain;Dept. Lenguajes y Ciencias de la Computación, ETSII Informática, Universidad de Málaga, Málaga, Spain;Dept. Lenguajes y Ciencias de la Computación, ETSII Informática, Universidad de Málaga, Málaga, Spain;Dept. Lenguajes y Ciencias de la Computación, ETSII Informática, Universidad de Málaga, Málaga, Spain;Dept. Lenguajes y Ciencias de la Computación, ETSII Informática, Universidad de Málaga, Málaga, Spain;Sección de Traumatología, Antequera, Hospital General de Antequera, Málaga, Spain;Sección de Traumatología, Antequera, Hospital General de Antequera, Málaga, Spain

  • Venue:
  • IWANN'05 Proceedings of the 8th international conference on Artificial Neural Networks: computational Intelligence and Bioinspired Systems
  • Year:
  • 2005

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Abstract

A proper gait assessment in patients with knee or hip injuries strongly determines the diagnosis and consequently the evolution of the pathology, the quality of life of implanted patients, and the overall costs involved. Among the different strategies to clinically assess gait, 3D optical tracking provides a reliable and objective evaluation. This method involves state-of-the-art image analysis that performs anatomical measurements upon bony landmarks identified by markers attached to the patient. We show how this technology can be used to perform patients diagnosis and follow-up by grouping the results of gait measurement with a competitive neural network where the number of clusters is automatically determined.