Literature DB >> 11205351

Optimal posture control of a musculo-skeletal arm model.

A C Schouten1, E de Vlugt, F C van der Helm, G G Brouwn.   

Abstract

In this paper maximal performance posture control of the human arm is investigated by means of model simulations. Recent experiments (F.C.T. van der Helm, submitted, 2000) have shown that the reflexive feedback during postural control varies with the bandwidth of the applied force disturbances. This paper focusses on the influence of the frequency content of force disturbances on the reflexive feedback gains by means of optimization. The arm is modelled by a nonlinear musculo-skeletal model with two degrees of freedom and six muscles. To facilitate the optimization of the model parameters, the arm model is linearized. A performance criterion is minimized for stochastic force disturbances in a two-step procedure: (1) optimization of static muscle activations using an additional energy criterion to obtain a unique and energy-efficient solution; antid (2) optimization of reflex gains using an additional control effort criterion to obtain a unique solution. The optimization reveals that for the given task and posture, the shoulder muscles have the largest contribution, whereas the bi-articular muscles have a relatively small contribution to the behaviour. The dynamics at the endpoint level are estimated so that a comparison can be made with the experiments. Compared to the experiments, the intrinsic damping of the model is relatively large (about 150%), whereas the intrinsic stiffness is relatively small (about 60%). These differences can be attributed to unmodelled mechanical effects of crossbridges in Hill-type muscle models. The optimized reflex gains show remarkable similarities with the values found in the experiments, implying that humans can adjust their reflexive feedback gains in an optimal way, weighting the performance and energy. The approach in this paper could be useful in the study of various posture tasks, for example in the prediction of the relation between the control parameters of various musculo-skeletal models and different experimental variables.

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Year:  2001        PMID: 11205351     DOI: 10.1007/s004220000202

Source DB:  PubMed          Journal:  Biol Cybern        ISSN: 0340-1200            Impact factor:   2.086


  10 in total

1.  ARMin: a robot for patient-cooperative arm therapy.

Authors:  Tobias Nef; Matjaz Mihelj; Robert Riener
Journal:  Med Biol Eng Comput       Date:  2007-08-03       Impact factor: 2.602

2.  Experimental measure of arm stiffness during single reaching movements with a time-frequency analysis.

Authors:  Davide Piovesan; Alberto Pierobon; Paul DiZio; James R Lackner
Journal:  J Neurophysiol       Date:  2013-08-14       Impact factor: 2.714

3.  Relating reflex gain modulation in posture control to underlying neural network properties using a neuromusculoskeletal model.

Authors:  Jasper Schuurmans; Frans C T van der Helm; Alfred C Schouten
Journal:  J Comput Neurosci       Date:  2010-09-24       Impact factor: 1.621

4.  EMG feedback tasks reduce reflexive stiffness during force and position perturbations.

Authors:  Patrick A Forbes; Riender Happee; Frans C T van der Helm; Alfred C Schouten
Journal:  Exp Brain Res       Date:  2011-06-30       Impact factor: 1.972

5.  Proximal versus distal control of two-joint planar reaching movements in the presence of neuromuscular noise.

Authors:  Hung P Nguyen; Jonathan B Dingwell
Journal:  J Biomech Eng       Date:  2012-06       Impact factor: 2.097

6.  Proprioceptive reflexes in patients with reflex sympathetic dystrophy.

Authors:  A C Schouten; W J T Van de Beek; J J Van Hilten; F C T Van der Helm
Journal:  Exp Brain Res       Date:  2003-05-13       Impact factor: 1.972

7.  Measuring multi-joint stiffness during single movements: numerical validation of a novel time-frequency approach.

Authors:  Davide Piovesan; Alberto Pierobon; Paul DiZio; James R Lackner
Journal:  PLoS One       Date:  2012-03-20       Impact factor: 3.240

8.  Identification of Object Dynamics Using Hand Worn Motion and Force Sensors.

Authors:  Henk G Kortier; H Martin Schepers; Peter H Veltink
Journal:  Sensors (Basel)       Date:  2016-11-26       Impact factor: 3.576

9.  Analysis of reflex modulation with a biologically realistic neural network.

Authors:  Arno H A Stienen; Alfred C Schouten; Jasper Schuurmans; Frans C T van der Helm
Journal:  J Comput Neurosci       Date:  2007-05-15       Impact factor: 1.621

10.  Use of self-selected postures to regulate multi-joint stiffness during unconstrained tasks.

Authors:  Randy D Trumbower; Matthew A Krutky; Bing-Shiang Yang; Eric J Perreault
Journal:  PLoS One       Date:  2009-05-01       Impact factor: 3.240

  10 in total

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