Non parametric identifier for Parkinson's disease dynamics by fuzzy-genetic controller

  • Authors:

  • Victor Ortiz;Cornelio Yáñez;Ángel Kuri;Ramon Miranda;Agustin Cabrera;Isaac Chairez

  • Affiliations:

  • Center for Computing Research, UPALM, Mexico;Center for Computing Research, UPALM, Mexico;Autonomous Technological Institute of Mexico, Tizapá, Mexico;UPIBI, Department Bioectronic, Laguna Ticoman, Mexico;UPIBI, Department Bioectronic, Laguna Ticoman, Mexico;UPIBI, Department Bioectronic, Laguna Ticoman, Mexico

  • Venue:
  • MOAS'07 Proceedings of the 18th conference on Proceedings of the 18th IASTED International Conference: modelling and simulation
  • Year:
  • 2007

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Abstract

Parkinson's disease often affects gait and mobility. To understand better the pathophysiology of this disease and to improve our ability to measure responses to therapeutic interventions, it may be helpful to control gait dynamics accurately. In to order to control this dynamics design to fuzzy controller, but the fuzzy identifier present to problem, in the heuristic selection of the values that describes the structure of the membership functions. To for numerical solution this disadvantage is the Genetic Algorithms. With this fuzzy-genetic controller it is managed to improve the dynamics of the disease of Parkinson's for his to better study in therapeutic interventions.