Discovering Similar Patterns for Characterizing Time Series in a Medical Domain

  • Authors:

  • Fernando Alonso;P. Caraça-Valente;Loïc Martínez;César Montes

  • Affiliations:

  • Polytechnic University Madrid, Department of Languages and Systems, Spain and Department of Languages and Systems, Polytechnic University Madrid, Campus de Montegancedo, 28660, Boadilla de Monte, ...;Polytechnic University Madrid, Department of Languages and Systems, Spain and Department of Languages and Systems, Polytechnic University Madrid, Campus de Montegancedo, 28660, Boadilla de Monte, ...;Polytechnic University Madrid, Department of Languages and Systems, Spain and Department of Languages and Systems, Polytechnic University Madrid, Campus de Montegancedo, 28660, Boadilla de Monte, ...;Polytechnic University Madrid, Department of Artificial Intelligence, Spain

  • Venue:
  • Knowledge and Information Systems
  • Year:
  • 2003

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Abstract

In this article, we describe the process of discovering similar patterns in time series and creating reference models for population groups in a medical domain, and particularly in the field of physiotherapy, using data mining techniques on a set of isokinetic data. The discovered knowledge was evaluated against the expertise of a physician specialized in isokinetic techniques, and applied in the I4 (Intelligent Interpretation of Isokinetic Information) project developed in conjunction with the Spanish National Center for Sports Research and Sciences for muscular diagnosis and rehabilitation, injury prevention, training evaluation and planning, etc., of elite athletes and ordinary people.