Fundamentals of Neuromechanics
Springer, 7 вер. 2015 р. - 194 стор.
This 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.
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2 Limb Kinematics
3 Limb Mechanics
4 TendonDriven Limbs
Part IIIntroduction to the Neural Controlof TendonDriven Limbs
5 The Neural Control of Joint Torques in TendonDriven Limbs Is Underdetermined
6 The Neural Control of Musculotendon Lengths and Excursions Is Overdetermined
7 Feasible Neural Commands and Feasible Mechanical Outputs
8 Feasible Neural Commands with Mechanical Constraints
Part IVNeuromechanics as a Scientific Tool
9 The Nature and Structure of Feasible Sets
Appendix APrimer on Linear Algebraand the Kinematics of Rigid Bodies
Part IIIFeasible Actions of TendonDriven Limbs
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activation space actuation algorithm anatomical angular velocities approach basis vectors Biomech biomechanical Biomed Biorobotics bounding box co-contraction column vectors computational geometry concepts convex polytope convex set coordination cost function define dimensionality dimensions direction eccentric contractions endpoint wrench equations example Exercises and Computer extensor F.J. Valero-Cuevas feasible activation set feasible force set feasible joint torque feasible neural commands feasible sets finger forward kinematic forward kinematic model frames of reference geometry high-dimensional IEEE inequality constraints J.J. Kutch Jacobian joint angles kinematic DOFs linear programming mapping mathematical Minkowski sum moment arm motor control multiple muscle activation muscle force muscle redundancy musculotendon N-cube nervous system neural control neuromuscular Neurosci optimization output wrench perspective planar plane polygon posture problem produce right hand rule rigid body robotic rotation scalar Sect shown in Fig solution space task tendon excursions tendon-driven limbs torque space torque-driven underdetermined vectormap versatility vertex vertices wrench space zonotope