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A Neural-based Model for the Control of the Arm During Planar Ballistic Movements

  • Silvia Conforto
  • Maurizio Schmid
  • Gianluca Gallo
  • Tommaso D’Alessio
  • Neri Accornero
  • Marco Capozza
Conference paper
Part of the CISM Courses and Lectures book series (CISM, volume 473)

Abstract

A software model simulating the learning process of planar ballistic movements of the arm was developed, using the following scheme: an artificial neural network (modelling the neural system), a pulse generator (a computational block driving the biomechanical model of the arm), a two degrees of freedom manipulator guided by a six-muscles model. The learning scheme was implemented in an unsupervised way, thus not back-propagating the error information on the arm final position with respect to the expected target, but associating movements between two space positions (network inputs) to muscular activations (network outputs). After a training consisting of about 45.000 simulated movements, the model reached a mean distance error consistent with the experimental data found in typical ballistic movements.

Keywords

Pulse Generator Online Correction Inverse Dynamic Problem Computational Block Neural Output 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Wien 2004

Authors and Affiliations

  • Silvia Conforto
    • 1
  • Maurizio Schmid
    • 1
  • Gianluca Gallo
    • 2
  • Tommaso D’Alessio
    • 2
  • Neri Accornero
    • 3
  • Marco Capozza
    • 3
  1. 1.Department of Mechanical and Industrial EngineeringUniversity Roma TreRomaItaly
  2. 2.Department of Applied ElectronicsUniversity Roma TreRomaItaly
  3. 3.Department of NeuroscienceUniversity La SapienzaRomaItaly

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