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This special issue comprises a selection of invited papers on numerical and computational modelling in neuromechanics and biomechanics based on presentations at the 13th International Symposium on Computer Simulation in Biomechanics, Leuven, Belgium, 30 June to 2 July 2011 and the XXIIIrd Congress of the International Society of Biomechanics, Brussels, Belgium, during 3–7 July 2011.

Research on numerical modelling of human movement and locomotion has been extensively focussing on the musculoskeletal system with excellent and powerful computational tools being developed. Although neurological control plays an equally important role in movement and balance as the musculoskeletal system itself, neuromechanics has received very limited attention in numerical and computational models to date. Indeed very timely is as such the overview and perspective on the role of neuromechanics in predicting muscle activation patterns for movement and balance by Ting et al. [1]. It is postulated that muscle coordination may be difficult or impossible to predict accurately based on biomechanical considerations alone because of redundancy in the musculoskeletal system. Because many solutions exist for any given movement, the role of the nervous system in further constraining muscle coordination patterns for movement must be considered in both healthy and impaired motor control. On the basis of computational neuromechanical analyses of experimental data combined with modelling techniques, Ting et al. have demonstrated several such neural constraints on the temporal and spatial patterns of muscle activity during both locomotion and postural responses to balance perturbations. Considering these findings in the context that, at present, computation of rigid-body dynamics, muscle forces and activation of the muscles are often performed separately, Bunderson et al. [2] present an intrinsically forward computational platform for neuromechanics. This platform explicitly represents the interdependencies among rigid body dynamics, frictional contact, muscle mechanics and neural control modules.

Praet et al. [3] developed a multibody computational model to study the musculoskeletal mechanics and dynamics of a seahorse tail towards biomimetic designs. The seahorse tail combines in an elegant way adequate bending flexibility to allow function as a prehensile organ while covered in protective armour providing radial stiffness. Insights in this intricate biomechanical system can offer novel designs for medical devices that require a combination of high bending flexibility and radial stiffness such as steerable catheters or flexible endovascular stents. The assessment of designs and structure–function relationships of endovascular stents is presented by Auricchio et al. [4]. This study is concerned with vessel scaffolding in carotid artery stenting which has implications on the likelihood of post-procedure complications such as stroke because of plaque debris. Finite element analysis with a patient-specific carotid artery geometry enabled to evaluate the degree of vessel scaffolding more realistically on deployed stent configurations compared with routinely employed free-expanded stent configurations.

Addressing the biomechanics of the diabetic foot, Fernandez et al.[5] and Mithraratne et al. [6] present a computational study in the area of metabolic diseases. Advanced diabetes mellitus involves reduced foot sensation because of peripheral neuropathy and poor circulation with end-points including foot ulcers, slow healing and amputation. By combining a continuum model of soft tissue stimulation [5] with a coupled solid–fluid model [6] based on patient-specific data, the authors investigated the role of increased stiffness of the plantar soft tissue observed in diabetic patients on blood transport and angiopathy in the main arteries of the foot.

REFERENCES

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  2. REFERENCES
  • 1
    Ting LH, Chvatal SA, Safavynia SA, Lucas McKay J.Review and perspective: Neuromechanical considerations for predicting muscle activation patterns for movement. International Journal for Numerical Methods in Biomedical Engineering 2012. DOI: 10.1002/cnm.2485.
  • 2
    Bunderson NE, Bingham JT, Hongchul Sohn M, Ting LH, Burkholder TJ.Neuromechanic: A computational platform for simulation and analysis of the neural control of movement. International Journal for Numerical Methods in Biomedical Engineering 2012. DOI: 10.1002/cnm.2486.
  • 3
    Praet T, Adriaens D, Van Cauter S, Masschaele B, De Beule M, Verhegghe B.Inspiration from nature: Dynamic modelling of the musculoskeletal structure of the seahorse tail. International Journal for Numerical Methods in Biomedical Engineering 2012. DOI: 10.1002/cnm.2499.
  • 4
    Auricchio F, Conti M, Ferraro M, Reali A.Evaluation of carotid stent scaffolding through patient-specific finite element analysis. International Journal for Numerical Methods in Biomedical Engineering 2012. DOI: 10.1002/cnm.2509.
  • 5
    Fernandez JW, Haque MA, Hunter PJ, Mithraratne K.Mechanics of the foot part 1: A continuum framework for evaluating soft tissue stiffening in the pathologic foot. International Journal for Numerical Methods in Biomedical Engineering 2012. DOI: 10.1002/cnm.2494.
  • 6
    Mithraratne K, Ho H, Hunter PJ, Fernandez JW.Mechanics of the foot part 2: A coupled solid-fluid model to investigate blood transport in the pathologic foot. International Journal for Numerical Methods in Biomedical Engineering 2012. DOI: 10.1002/cnm.2493.