Motion control via muscle synergies: application to throwing

In the current paper, we present a control method based on muscle synergy extraction and adaptation to drive a human arm in a direct dynamics simulation of an overhead throwing motion. The experimental protocol for synergy extraction and model are first presented, followed by a control method consisting of a series of optimizations to adapt muscle parameters and synergies to match experimental data. Results show that the motion can be accurately reproduced thanks to the muscle synergy extraction and adaptation to the model.

[1]  Taesoo Kwon,et al.  Locomotion control for many-muscle humanoids , 2014, ACM Trans. Graph..

[2]  Eftychios Sifakis,et al.  Realistic Biomechanical Simulation and Control of Human Swimming , 2014, ACM Trans. Graph..

[3]  Vladlen Koltun,et al.  Optimizing locomotion controllers using biologically-based actuators and objectives , 2012, ACM Trans. Graph..

[4]  Michiel van de Panne,et al.  Flexible muscle-based locomotion for bipedal creatures , 2013, ACM Trans. Graph..

[5]  Andreas Daffertshofer,et al.  Removing ECG contamination from EMG recordings: a comparison of ICA-based and other filtering procedures. , 2012, Journal of electromyography and kinesiology : official journal of the International Society of Electrophysiological Kinesiology.

[6]  Franck Plestan,et al.  Distribution of forces between synergistics and antagonistics muscles using an optimization criterion depending on muscle contraction behavior. , 2010, Journal of biomechanical engineering.

[7]  C Pontonnier,et al.  Identifying representative muscle synergies in overhead football throws , 2015, Computer methods in biomechanics and biomedical engineering.

[8]  A. J. van den Bogert,et al.  Direct dynamics simulation of the impact phase in heel-toe running. , 1995, Journal of biomechanics.

[9]  Stefano Panzeri,et al.  Muscle synergies in neuroscience and robotics: from input-space to task-space perspectives , 2013, Front. Comput. Neurosci..

[10]  David G Lloyd,et al.  Neuromusculoskeletal modeling: estimation of muscle forces and joint moments and movements from measurements of neural command. , 2004, Journal of applied biomechanics.

[11]  J. Hodgins,et al.  Animating Human Athletes , 1998 .

[12]  Hartmut Geyer,et al.  A Muscle-Reflex Model That Encodes Principles of Legged Mechanics Produces Human Walking Dynamics and Muscle Activities , 2010, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[13]  O. Schmitt The heat of shortening and the dynamic constants of muscle , 2017 .

[14]  Walter Herzog,et al.  Model-based estimation of muscle forces exerted during movements. , 2007, Clinical biomechanics.

[15]  Ludovic Hoyet,et al.  Perceptual Evaluation of Motion Editing for Realistic Throwing Animations , 2014, TAP.

[16]  Hyunsoo Kim,et al.  Nonnegative Matrix Factorization Based on Alternating Nonnegativity Constrained Least Squares and Active Set Method , 2008, SIAM J. Matrix Anal. Appl..

[17]  Bruno Arnaldi,et al.  Morphology‐independent representation of motions for interactive human‐like animation , 2005, Comput. Graph. Forum.

[18]  Gentiane Venture,et al.  Identifying musculo-tendon parameters of human body based on the musculo-skeletal dynamics computation and Hill-Stroeve muscle model , 2005, 5th IEEE-RAS International Conference on Humanoid Robots, 2005..

[19]  A. Muller,et al.  A Simple Method to Calibrate Kinematical Invariants: Application to Overhead Throwing , 2015 .

[20]  Nicolas Pronost,et al.  Interactive Character Animation Using Simulated Physics: A State‐of‐the‐Art Review , 2012, Comput. Graph. Forum.

[21]  Gentiane Venture,et al.  APPLICATION OF NON-LINEAR LEAST SQUARE METHOD TO ESTIMATE THE MUSCLE DYNAMICS OF THE ELBOW JOINT , 2006 .

[22]  Scott L. Delp,et al.  A Model of the Upper Extremity for Simulating Musculoskeletal Surgery and Analyzing Neuromuscular Control , 2005, Annals of Biomedical Engineering.

[23]  Francesco Lacquaniti,et al.  Control of reaching movements by muscle synergy combinations , 2013, Front. Comput. Neurosci..

[24]  David C. Brogan,et al.  Animating human athletics , 1995, SIGGRAPH.

[25]  Matthew C. Tresch,et al.  The number and choice of muscles impact the results of muscle synergy analyses , 2013, Front. Comput. Neurosci..

[26]  Vladlen Koltun,et al.  Animating human lower limbs using contact-invariant optimization , 2013, ACM Trans. Graph..

[27]  KangKang Yin,et al.  SIMBICON: simple biped locomotion control , 2007, ACM Trans. Graph..

[28]  C Pontonnier,et al.  A bio-inspired limb controller for avatar animation , 2014, Computer methods in biomechanics and biomedical engineering.

[29]  L. Chèze,et al.  Adjustments to McConville et al. and Young et al. body segment inertial parameters. , 2007, Journal of biomechanics.

[30]  John Rasmussen,et al.  A generic detailed rigid-body lumbar spine model. , 2007, Journal of biomechanics.

[31]  H. Hermens,et al.  European recommendations for surface electromyography: Results of the SENIAM Project , 1999 .

[32]  H F J M Koopman,et al.  Morphological muscle and joint parameters for musculoskeletal modelling of the lower extremity. , 2005, Clinical biomechanics.

[33]  Georges Dumont,et al.  Dynamics-based analysis and synthesis of human locomotion , 2007, The Visual Computer.

[34]  A Muller,et al.  Dealing with modularity of multibody models , 2015, Computer methods in biomechanics and biomedical engineering.