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Model-Based Sensorimotor Integration for Multi-Joint Control: Development of a Virtual Arm Model
Biomedical Engineering, University of Southern California (USC), Los Angeles, USA.
2008 (English)In: Annals of Biomedical Engineering, ISSN 0090-6964, E-ISSN 1573-9686, Vol. 36, no 6, 1033-1048 p.Article in journal (Refereed) Published
Abstract [en]

An integrated, sensorimotor virtual arm (VA) model has been developed and validated for simulation studies of control of human arm movements. Realistic anatomical features of shoulder, elbow and forearm joints were captured with a graphic modeling environment, SIMM. The model included 15 musculotendon elements acting at the shoulder, elbow and forearm. Muscle actions on joints were evaluated by SIMM generated moment arms that were matched to experimentally measured profiles. The Virtual Muscle (TM) (VM) model contained appropriate admixture of slow and fast twitch fibers with realistic physiological properties for force production. A realistic spindle model was embedded in each VM with inputs of fascicle length, gamma static (gamma(stat)) and dynamic (gamma(dyn)) controls and outputs of primary (I-a) and secondary (II) afferents. A piecewise linear model of Golgi Tendon Organ (GTO) represented the ensemble sampling (I-b) of the total muscle force at the tendon. All model components were integrated into a Simulink block using a special software tool. The complete VA model was validated with open-loop simulation at discrete hand positions within the full range of alpha and gamma drives to extrafusal and intrafusal muscle fibers. The model behaviors were consistent with a wide variety of physiological phenomena. Spindle afferents were effectively modulated by fusimotor drives and hand positions of the arm. These simulations validated the VA model as a computational tool for studying arm movement control. The VA model is available to researchers at website

Place, publisher, year, edition, pages
New York: Springer, 2008. Vol. 36, no 6, 1033-1048 p.
Keyword [en]
computational models; joints; muscles; spindles; GTO; sensorimotor control; simulation; Matlab and Simulink
National Category
Computer and Information Science
URN: urn:nbn:se:kth:diva-55486DOI: 10.1007/s10439-008-9461-8ISI: 000255744800014OAI: diva2:471699
QC 20120110Available from: 2012-01-02 Created: 2012-01-02 Last updated: 2012-01-10Bibliographically approved

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Song, Dan
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