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020 _a9781447167471
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024 7 _a10.1007/978-1-4471-6747-1
_2doi
050 4 _aTJ212-225
050 4 _aTJ210.2-211.495
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072 7 _aTEC004000
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072 7 _aTJFM
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082 0 4 _a629.8
_223
100 1 _aValero-Cuevas, Francisco J.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_962693
245 1 0 _aFundamentals of Neuromechanics
_h[electronic resource] /
_cby Francisco J. Valero-Cuevas.
250 _a1st ed. 2016.
264 1 _aLondon :
_bSpringer London :
_bImprint: Springer,
_c2016.
300 _aXXIV, 194 p. 65 illus.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aBiosystems & Biorobotics,
_x2195-3570 ;
_v8
520 _aThis book provides a conceptual and computational framework to study how the nervous system exploits the anatomical properties of limbs to produce mechanical function. The study of the neural control of limbs has historically emphasized the use of optimization to find solutions to the muscle redundancy problem. That is, how does the nervous system select a specific muscle coordination pattern when the many muscles of a limb allow for multiple solutions? I revisit this problem from the emerging perspective of neuromechanics that emphasizes finding and implementing families of feasible solutions, instead of a single and unique optimal solution. Those families of feasible solutions emerge naturally from the interactions among the feasible neural commands, anatomy of the limb, and constraints of the task. Such alternative perspective to the neural control of limb function is not only biologically plausible, but sheds light on the most central tenets and debates in the fields of neural control, robotics, rehabilitation, and brain-body co-evolutionary adaptations. This perspective developed from courses I taught to engineers and life scientists at Cornell University and the University of Southern California, and is made possible by combining fundamental concepts from mechanics, anatomy, mathematics, robotics and neuroscience with advances in the field of computational geometry. Fundamentals of Neuromechanics is intended for neuroscientists, roboticists, engineers, physicians, evolutionary biologists, athletes, and physical and occupational therapists seeking to advance their understanding of neuromechanics. Therefore, the tone is decidedly pedagogical, engaging, integrative, and practical to make it accessible to people coming from a broad spectrum of disciplines. I attempt to tread the line between making the mathematical exposition accessible to life scientists, and convey the wonder and complexity of neuroscience to engineers and computational scientists. While no one approach can hope to definitively resolve the important questions in these related fields, I hope to provide you with the fundamental background and tools to allow you to contribute to the emerging field of neuromechanics.
650 0 _aControl engineering.
_931970
650 0 _aRobotics.
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650 0 _aAutomation.
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650 0 _aComputer simulation.
_95106
650 0 _aNeurosciences.
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650 0 _aBioinformatics.
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650 0 _aAlgebraic geometry.
_962694
650 0 _aEvolution (Biology).
_916952
650 1 4 _aControl, Robotics, Automation.
_931971
650 2 4 _aComputer Modelling.
_962695
650 2 4 _aNeuroscience.
_934310
650 2 4 _aComputational and Systems Biology.
_931619
650 2 4 _aAlgebraic Geometry.
_962696
650 2 4 _aEvolutionary Biology.
_934708
710 2 _aSpringerLink (Online service)
_962697
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9781447167464
776 0 8 _iPrinted edition:
_z9781447167488
776 0 8 _iPrinted edition:
_z9781447170891
830 0 _aBiosystems & Biorobotics,
_x2195-3570 ;
_v8
_962698
856 4 0 _uhttps://doi.org/10.1007/978-1-4471-6747-1
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