@article {960, title = {Predictive multibody dynamic simulation of human neuromusculoskeletal systems: a review}, journal = {Multibody System Dynamics}, year = {2022}, month = {11/2022}, keywords = {Biomechanics, Human movement, Neuromusculoskeletal system models, Optimal Control, Predictive dynamic simulation, Review}, doi = {https://doi.org/10.1007/s11044-022-09852-x}, author = {M{\'\i}riam Febrer-Nafr{\'\i}a and Ali Nasr and Mahdokht Ezati and Peter Brown and Josep M. Font-Llagunes and John McPhee} } @inproceedings {936, title = {Simulating Human Upper and Lower Limb Balance Recovery Responses Using Nonlinear Model Predictive Control}, booktitle = {Annual International Conference of the IEEE Engineering in Medicine \& Biology Society (EMBC)}, year = {2021}, month = {12/2021}, publisher = {IEEE}, organization = {IEEE}, address = {Mexico}, abstract = {

The ability to generate predictive dynamic simulations of human movement using optimal control has been a growing point of interest in the design of medical/assistive devices, e.g. robotic exoskeletons. Despite this, many disseminated simulations of whole-body tasks, such as balance recovery, neglect the role of the upper body instead focusing on postural joints, e.g. ankle, knees, hips. Thus, the purpose of the current study was to use a novel nonlinear model predictive control (NMPC) approach to assess how actuated upper limbs, as well as different individual performance (optimality) criteria, can shape simulated reactive balance recovery responses. A sagittal biomechanical model of a young adult standing was designed and actuated via nonlinear muscle torque generators (rotational single-muscle equivalents). Forward dynamic simulations of balance recovery (NMPC-driven) following an unexpected support-surface perturbation were generated for each unique combination of selected performance criteria (6 total), perturbation direction (forward and backward), and arm joints free/locked. The observed joint trajectories provide insight into the emergence of human elements of postural control from individual optimality criteria, e.g. hip-ankle strategies emerge from single-joint regulation. Quantitative analysis of performance improvements with the arms free suggest that whether arm responses emerge in the simulations may be dependent on the problem\’s initial guess. Future work should focus on testing further performance criteria and improving NMPC as a model of the nervous system.

}, keywords = {Arms, Biological system modeling, Biomechanics, Optimal Control, Perturbation methods, Predictive models}, doi = {10.1109/EMBC46164.2021.9630208}, url = {https://ieeexplore.ieee.org/abstract/document/9630208}, author = {Inkol, Keaton A. and McPhee, John} } @article {887, title = {Predictive Dynamic Simulation of Olympic Track Cycling Standing Start Using Direct Collocation Optimal Control}, journal = {Multibody System Dynamics}, year = {2020}, abstract = {

Much of the previous research on modeling and simulation of cycling has focused on seated pedaling, modeling the crank load with an effective resistive torque and inertia. This study focuses on modeling standing starts, a component of certain track cycling events in which the cyclist starts from rest and attempts to accelerate to top speed as quickly as possible. A ten degree-of-freedom, two-legged cyclist and bicycle model was developed and utilized for predictive dynamic simulations of standing starts. Experimental data including crank torque, cadence, and joint kinematics were collected for a member of the Canadian Olympic team performing standing starts on the track. Using direct collocation optimal control to maximize the simulated distance traveled, the predictive simulations aligned well with the experiments and replicated key aspects of the standing start technique such as the drive and reset. The model\’s use in \“What if?\” scenarios presents interesting possibilities for investigating optimal techniques and equipment in cycling.\ 

}, keywords = {Optimal Control, Sports Biomechanics, Sports Engineering}, issn = {1573-272X}, doi = {10.1007/s11044-020-09723-3}, url = {https://link.springer.com/article/10.1007/s11044-020-09723-3}, author = {Conor Jansen and John McPhee} } @article {888, title = {Predictive Forward Dynamic Simulation of Manual Wheelchair Propulsion on a Rolling Dynamometer}, journal = {ASME Journal of Biomechanical Engineering}, year = {2020}, abstract = {

Research studies to understand the biomechanics of manual wheelchair propulsion often incorporate experimental data and mathematical models. This project aimed to advance this field of study by developing a two-dimensional model to generate first of its kind forward dynamic fully predictive computer simulations of a wheelchair basketball athlete on a stationary ergometer. Subject-specific parameters and torque generator functions were implemented in the model from dual x-ray absorptiometry and human dynamometer measurements. A direct collocation optimization method was used in a wheelchair propulsion model for the first time to replicate the human muscle recruitment strategy. Simulations were generated for varying time constraints and seat positions. Similar magnitudes of kinematic and kinetic data were observed between simulation and experimental data of a first push. Furthermore, seat heights inferior to the neutral position were found to produce similar joint torques to those reported in previous studies. An anterior seat placement produced the quickest push time with the least amount of shoulder torque required. The work completed in this project demonstrates that fully predictive simulations of wheelchair propulsion have the potential of varying simulation parameters to draw meaningful conclusions.

}, keywords = {Biomechanics, Optimal Control, Predictive Simulation, Sports Engineering, Wheelchair}, doi = {10.1115/1.4046298}, url = {https://asmedigitalcollection.asme.org/biomechanical/article/doi/10.1115/1.4046298/1074477/Predictive-Forward-Dynamic-Simulation-of-Manual}, author = {Colin Brown and John McPhee} } @article {847, title = {Constrained Dynamic Optimization of Sit-To-Stand Motion Driven by B{\'e}zier Curves}, journal = {ASME Journal of Biomechanical Engineering}, year = {2018}, type = {Journal Article}, abstract = {

The purpose of this work is two-fold: first, to synthesize a motion pattern imitating sit-to-stand and second, to compare the kinematics and dynamics of the resulting motion to healthy sit-to-stand. Predicting sit-to-stand in simulation inspired the creation of three models: a biomechanical model, a motion model, and performance criteria as a model of preference. First, the human is represented as three rigid links in the sagittal plane. This model captures aspects of joint, foot, and buttocks physiology, which makes it the most comprehensive planar model for predicting sit-to-stand to date. Second, candidate sit-to-stand trajectories are described geometrically by a set of B{\'e}zier curves which seem well suited to predictive biomechanical simulations. Third, with the assumption that healthy people naturally prioritize mechanical efficiency, disinclination to a motion is described as a cost function of joint torques, and for the first time, physical infeasibility including slipping and falling. This new dynamic optimization routine allows for motions of gradually increasing complexity while the model\’s performance is improving. Using these models and optimal control strategy together has produced gross motion patterns characteristic of healthy sit-to-stand when compared with normative data from the literature.

}, keywords = {Biomechanics, Dynamics, Kinematics, Mechanical efficiency, Mechanics, Optimal Control, Optimization, Physiology, Preferences, Simulation}, doi = {10.1115/1.4041527}, url = {http://biomechanical.asmedigitalcollection.asme.org/article.aspx?articleid=2703965}, author = {V Norman-Gerum}, editor = {John McPhee} } @article {841, title = {Optimization-Based Motor Control of a Paralympic Wheelchair Athlete}, journal = {Sports Engineering}, volume = {21}, year = {2018}, abstract = {

The following research approximated how the central nervous system of Paralympic wheelchair athletes resolve kinematic redundancies during upper-limb movements. A multibody biomechanical model of a tetraplegic Paralympic athlete was developed using subject-specific body segment parameters. The angular joint kinematics throughout a specified Paralympic sport movement (i.e., wheelchair curling) were experimentally measured using inertial measurement units. The motor control system of the Paralympian was mathematically modelled and simulated using forward dynamics optimization. The predicted kinematics from different optimization objective functions (i.e., minimizing resultant joint moments, mechanical joint power, and angular joint velocities and accelerations) were compared with those experimentally measured throughout the wheelchair curling movement. Of the optimization objective functions under consideration, minimizing angular joint accelerations produced the most accurate predictions of the kinematic trajectories (i.e., characterized with the lowest overall root mean square deviations) and the shortest optimization computation time. The implications of these control findings are discussed with regards to optimal wheelchair design through predictive dynamic simulations.

}, keywords = {Forward Dynamics Modelling, Human Motor Control, Optimal Control, Optimization, Sports Biomechanics, Sports Engineering}, issn = {1460-2687}, doi = {10.1007/s12283-018-0265-2}, url = {https://link.springer.com/article/10.1007/s12283-018-0265-2}, author = {Brokoslaw Laschowski and Naser Mehrabi and John McPhee} }