Human Muscle-Tendon Stiffness Estimation During Normal Gait Cycle Based on Gaussian Mixture Model

  • Roberto Bortoletto
  • Stefano Michieletto
  • Enrico Pagello
  • Davide Piovesan
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 302)


The aim of this study is to estimate the stiffness of the muscle-tendon unit, of human lower limb, during the execution of a normal gait cycle. Unlike the analytical techniques already widely validated in literature and discussed below, a probabilistic approach based on the Gaussian Mixture Model (GMM) has been adopted here for the computation of the muscle-tendon unit stiffness. The obtained results for the major muscle groups are shown. The effectiveness of the proposed approach has been evaluated by computing the Root Mean Square (RMS) error between the stiffness calculated analytically and those calculated using the GMM, for each subject.


Gaussian mixture model Muscle stiffness Gait cycle 



This research has been supported by “Consorzio Ethics” through a grant for research activity on the project “Rehabilitation Robotics”, and by the Faculty research grant at Gannon University.


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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Roberto Bortoletto
    • 1
  • Stefano Michieletto
    • 1
  • Enrico Pagello
    • 1
  • Davide Piovesan
    • 2
  1. 1.Intelligent Autonomous Systems Laboratory (IAS-Lab), Department of Information EngineeringUniversity of PaduaPaduaItaly
  2. 2.Biomedical Program, Mechanical Engineering DepartmentGannon UniversityErieUSA

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