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Radial Basis Gaussian Functions for Modelling Motor Learning Process of Human Arm Movement in the Ballistic Task – Hit a Target

  • Slobodan LuburaEmail author
  • Dejan Ž. Jokić
  • Goran S. Đorđević
Conference paper
Part of the Lecture Notes in Networks and Systems book series (LNNS, volume 59)

Abstract

Mathematical tool for modelling motor learning of human arm movement in the ballistic task – hit a target is described in this paper. Proposed tool is used for quantification of the subject’s ability to learn motor control of their arm movements in the ballistic task after training. Conducted research showed that the key role in the ballistic task – hit the target had velocity profiles of the arm/joystick movement. Therefore, the velocity profiles have been an object of refined analysis and modelling performed for the purpose of determining whether motor learning of humans arm movement is possible or not. Radial Basis Gaussian Functions (RBGF) are used as a tool for analysis and modelling, because they can reveal behaviour of human’s arm movement around more local points or in the more stages of movement. The proposed tool is verified by conducted experimental analysis. The experimental analysis was performed as practice of 50 subjects in the ballistic task – hit a target.

Keywords

Radial Basis Gaussian Function Human arm Motor learning Ballistic task 

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Slobodan Lubura
    • 1
    Email author
  • Dejan Ž. Jokić
    • 2
  • Goran S. Đorđević
    • 3
  1. 1.Faculty of Electrical EngineeringUniversity of East SarajevoEast SarajevoBosnia and Herzegovina
  2. 2.International Burch UniversitySarajevoBosnia and Herzegovina
  3. 3.Faculty of Electronic EngineeringUniversity of NišNišSerbia

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