Optimal or antagonistic? muscle force solutions in the lower limb

Provides evidence of the appropriateness of different muscle force distribution protocols in a musculoskeletal model of the lower limb

Biomechanical musculoskeletal model

Předkládaná práce je zaměřena na svalově-kosterní modelování, především pak na výpočet svalových sil a ramen momentů při libovolném pohybu s využitím nové metody určení průběhů svalů. Jejím hlavním přínosem je vývoj unikátní metody založené na svalovém obepínání anuloidů, která výrazné snižuje nedostatky již existujících metod pro určení svalových trajektorií. Metoda je vyvinuta pro výpočet korektního tvaru svalu při jakékoliv konfiguraci kloubů. Je založena na obecné známé metodě svalového obepínání série překážek tvořených tuhými geometrickými tvary a nahrazujících okolní tkáně, obecné známá jako metoda obstacle-set. Z důvodu vylepšení původní metody byly překážky tvaru koule či válce nahrazeny anuloidy. Nové vzniklá metoda dále umožňuje automatický výpočet umístění svalových úponů; pozic, natočení a poloměrů jednotlivých anuloidů; nárůst aktuálního fyziologického průřezu svalu během kontrakce či změny tvaru svalu s ohledem na sousedící svalové skupiny. Veškerá geometrie metody je založena na MRI a počtu uvažovaných svalových vláken. Dílčím cílem studie je vytvořit jednoduchý model ramene v programu MATLAB, který obsahuje pouze dvojhlavý sval pažní a je založen na nové vyvinuté metodě obepínání anuloidu. Touto cestou je prezentována implementace, použití, výhody a nevýhody této metody. Kosti modelu jsou nahrazeny tuhými tělesy spojenými reálnými klouby; skutečné chování svalů je simulováno modelem Hillova typu. Pro potřeby této práce jsou pohyby lopatky a klíční kosti zanedbány. Svalový komplex je prezentován elastickými svalovými vlákny zanedbatelného tření generující stejnou sílu po celé své délce a obepínající sousední struktury nahrazené anuloidy. Pro validaci modelu a metody obepínání anuloidu je simulován pohyb pažní kosti - abdukce a přední flexe do úhlu 90°. Trajektorie svalových vláken, síly ve svalech, aktuální délka a momentová ramena svalů jsou poté porovnána s výsledky obdobných modelů prezentovaných v literatuře, s elektromyografickým měřením a se dvěma modely ramene sestavených v programu AnyBody Modeling System. Výsledky prokazují úspěšnou validaci hlavních akčních členů abdukce a přední flexe ramene. Nová metoda svalového obepínání anuloidů je vhodnou metodou pro simulaci všech kloubů lidského těla - především pro komplikované klouby jako je např. ramenní komplex, či pro všechny typy svalů - silný, slabý, plochý, dlouhý, krátký, aj. Prezentovaná studie také stručné představuje anatomii a fyziologii ramenního komplexu, nabízí rešerši existujících ramenních modelů a metod pro výpočet svalové trajektorie a do větších detailů popisuje dynamiku vázaných mechanických systémů v prostoru. Závěrem lze říci, že metoda svalového obepínání anuloidů je užitečným nástrojem při svalové-kosterním modelování.NeobhájenoPresented thesis work is focused on musculoskeletal modeling, especially on muscle forces and moment arms calculation using the new method for muscle path determination. This method is based on obstacle-set method. However, the new torus obstacles are implemented instead of standard obstacles such as spheres and cylinders to improve the original process of muscle wrapping. This method also enables the automatic calculation of muscle lines attachments; positions, rotation and radius of torus obstacles originated from MRI and respecting the input number of muscle lines set by the user. The torus-obstacle method also considers the muscle bulging up as well as changes of muscle shapes influenced by surrounding muscles. The case of this study is to create the simple shoulder model in MATLAB including the deltoid muscle and using developed torus-obstacle method. Thanks that, the implementation, usage, advantages and disadvantages of presented method are shown. The bones are modeled by rigid bodies connected by real joints; the real muscle behavior is simulated by Hill-type model. For purpose of this work, the scapula and the clavicle are fixed. The muscle complex is replaced by elastic frictionless muscle lines of action generating the same force along the whole band and wrapping around the neighboring structures replaced by torus obstacles. The humeral abduction and forward flexion till 90° are simulated to validate the model and also the wrapping method. The paths of muscle lines, muscle forces, actual lengths and the muscle moment arms are compared to the similar models published in literature, to the electromyography measurement and to two shoulder models built in AnyBody Modeling System. The results show the successful validation of major actuators of abduction and forward flexion. In addition, the method is absolutely not time-consuming. The new torus-obstacle method is suitable for all human body joints - especially for complicated joints as shoulder complex, for all muscles - thick, thin, shallow, long, short etc. Presented study also introduces briefly the anatomy and physiology of the shoulder complex, offers the research of existing shoulder models and methods for muscle path definition and describes the multibody spatial dynamics in more details. In conclusion, developed torus-obstacle method designed for muscle trajectory computation in musculoskeletal modeling seems to be useful tool

Learning to Run challenge solutions: Adapting reinforcement learning methods for neuromusculoskeletal environments

In the NIPS 2017 Learning to Run challenge, participants were tasked with building a controller for a musculoskeletal model to make it run as fast as possible through an obstacle course. Top participants were invited to describe their algorithms. In this work, we present eight solutions that used deep reinforcement learning approaches, based on algorithms such as Deep Deterministic Policy Gradient, Proximal Policy Optimization, and Trust Region Policy Optimization. Many solutions use similar relaxations and heuristics, such as reward shaping, frame skipping, discretization of the action space, symmetry, and policy blending. However, each of the eight teams implemented different modifications of the known algorithms.Comment: 27 pages, 17 figure

Upper limb strength estimation of physically impaired persons using a musculoskeletal model: A sensitivity analysis

© 2015 IEEE. Sensitivity of upper limb strength calculated from a musculoskeletal model was analyzed, with focus on how the sensitivity is affected when the model is adapted to represent a person with physical impairment. Sensitivity was calculated with respect to four muscle-tendon parameters: muscle peak isometric force, muscle optimal length, muscle pennation, and tendon slack length. Results obtained from a musculoskeletal model of average strength showed highest sensitivity to tendon slack length, followed by muscle optimal length and peak isometric force, which is consistent with existing studies. Muscle pennation angle was relatively insensitive. The analysis was repeated after adapting the musculoskeletal model to represent persons with varying severities of physical impairment. Results showed that utilizing the weakened model significantly increased the sensitivity of the calculated strength at the hand, with parameters previously insensitive becoming highly sensitive. This increased sensitivity presents a significant challenge in applications utilizing musculoskeletal models to represent impaired individuals

Musculoskeletal modelling of an ostrich (Struthio camelus) pelvic limb: influence of limb orientation on muscular capacity during locomotion

We developed a three-dimensional, biomechanical computer model of the 36 major pelvic limb muscle groups in an ostrich (Struthio camelus) to investigate muscle function in this, the largest of extant birds and model organism for many studies of locomotor mechanics, body size, anatomy and evolution. Combined with experimental data, we use this model to test two main hypotheses. We first query whether ostriches use limb orientations (joint angles) that optimize the moment-generating capacities of their muscles during walking or running. Next, we test whether ostriches use limb orientations at mid-stance that keep their extensor muscles near maximal, and flexor muscles near minimal, moment arms. Our two hypotheses relate to the control priorities that a large bipedal animal might evolve under biomechanical constraints to achieve more effective static weight support. We find that ostriches do not use limb orientations to optimize the moment-generating capacities or moment arms of their muscles. We infer that dynamic properties of muscles or tendons might be better candidates for locomotor optimization. Regardless, general principles explaining why species choose particular joint orientations during locomotion are lacking, raising the question of whether such general principles exist or if clades evolve different patterns (e.g., weighting of muscle force–length or force–velocity properties in selecting postures). This leaves theoretical studies of muscle moment arms estimated for extinct animals at an impasse until studies of extant taxa answer these questions. Finally, we compare our model’s results against those of two prior studies of ostrich limb muscle moment arms, finding general agreement for many muscles. Some flexor and extensor muscles exhibit self-stabilization patterns (posture-dependent switches between flexor/extensor action) that ostriches may use to coordinate their locomotion. However, some conspicuous areas of disagreement in our results illustrate some cautionary principles. Importantly, tendon-travel empirical measurements of muscle moment arms must be carefully designed to preserve 3D muscle geometry lest their accuracy suffer relative to that of anatomically realistic models. The dearth of accurate experimental measurements of 3D moment arms of muscles in birds leaves uncertainty regarding the relative accuracy of different modelling or experimental datasets such as in ostriches. Our model, however, provides a comprehensive set of 3D estimates of muscle actions in ostriches for the first time, emphasizing that avian limb mechanics are highly three-dimensional and complex, and how no muscles act purely in the sagittal plane. A comparative synthesis of experiments and models such as ours could provide powerful synthesis into how anatomy, mechanics and control interact during locomotion and how these interactions evolve. Such a framework could remove obstacles impeding the analysis of muscle function in extinct taxa

Real-time simulation of three-dimensional shoulder girdle and arm dynamics

Electrical stimulation is a promising technology for the restoration of arm function in paralyzed individuals. Control of the paralyzed arm under electrical stimulation, however, is a challenging problem that requires advanced controllers and command interfaces for the user. A real-time model describing the complex dynamics of the arm would allow user-in-the-loop type experiments where the command interface and controller could be assessed. Real-time models of the arm previously described have not included the ability to model the independently controlled scapula and clavicle, limiting their utility for clinical applications of this nature. The goal of this study therefore was to evaluate the performance and mechanical behavior of a real-time, dynamic model of the arm and shoulder girdle. The model comprises seven segments linked by eleven degrees of freedom and actuated by 138 muscle elements. Polynomials were generated to describe the muscle lines of action to reduce computation time, and an implicit, first-order Rosenbrock formulation of the equations of motion was used to increase simulation step-size. The model simulated flexion of the arm faster than real time, simulation time being 92% of actual movement time on standard desktop hardware. Modeled maximum isometric torque values agreed well with values from the literature, showing that the model simulates the moment-generating behavior of a real human arm. The speed of the model enables experiments where the user controls the virtual arm and receives visual feedback in real time. The ability to optimize potential solutions in simulation greatly reduces the burden on the user during development

Personalized hip joint kinetics during deep squatting in young, athletic adults

The goal of this study was to report deep squat hip kinetics in young, athletic adults using a personalized numerical model solution based on inverse dynamics. Thirty-five healthy subjects underwent deep squat motion capture acquisitions and MRI scans of the lower extremities. Musculoskeletal models were personalized using each subject's lower limb anatomy. The average peak hip joint reaction force was 274 percent bodyweight. Average peak hip and knee flexion angles were 107 degrees and 112 degrees respectively. These new findings show that deep squatting kinetics in the younger population differ substantially from the previously reported in vivo data in older subjects

Lower limb stiffness estimation during running: the effect of using kinematic constraints in muscle force optimization algorithms

The focus of this paper is on the effect of muscle force optimization algorithms on the human lower limb stiffness estimation. By using a forward dynamic neuromusculoskeletal model coupled with a muscle short-range stiffness model we computed the human joint stiffness of the lower limb during running. The joint stiffness values are calculated using two different muscle force optimization procedures, namely: Toque-based and Torque/Kinematic-based algorithm. A comparison between the processed EMG signal and the corresponding estimated muscle forces with the two optimization algorithms is provided. We found that the two stiffness estimates are strongly influenced by the adopted algorithm. We observed different magnitude and timing of both the estimated muscle forces and joint stiffness time profile with respect to each gait phase, as function of the optimization algorithm used