Browsing by Author "Häufle, Daniel F. B."

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Open Access
Contraction dynamics of biological muscles : mechanical and thermodynamical prediction, and experimental verification
(2013) Häufle, Daniel F. B.; Wunner, Günter (Prof. Dr.)
Biological movement generation is a dynamical process involving not only biomechanical structures, e.g., muscles, bones, ligaments, etc. but also metabolic energy processing, physiological sensing, and neuronal control. In this thesis, a physics approach to study these complex interactions is presented. It builds upon the results of physiological experiments with isolated animal muscles over the course of which their distinct dynamic properties have been described in great detail. Derived from previous simulation studies, the hypotheses posed were that the dynamic properties of muscles strongly contribute to generation and control of movements, they allow very simple control strategies, and thus reduce control effort in comparison to (technical) systems whose actuators do not have similar dynamic properties. Hopping was used as a template model to study the relation of muscle properties, control strategies, and interaction with the environment. It was found that the typical non-linear force-velocity relation of the biological muscle is important for hopping stability. Additionally, stability could be improved by combining feed-forward and feedback control strategies. The results highlight the importance of the muscle properties, especially that of the force-velocity relation for the control of periodic movements. If an organism exploits the muscle properties, the control effort was expected to be less than in a (technical) system without these properties. To quantify control effort, a new measure based on information theory was developed. Applied to hopping models this method revealed that the required information to control hopping can be as low as I=34bit with a muscle vs. I=798bit with a DC-motor. Concerning the muscle, the control strategy was particularly designed to exploit the muscle properties. In case of the DC-motor, a typical engineering control approach was chosen, where a negative-feedback controller was used to enforce a predefined trajectory regardless of the actuator properties. This shows that the approach to control effort based on information theory is applicable to and comparable across completely different actuator designs and control approaches. So far, biomechanical muscle models incorporated the force-velocity relation as a phenomenological fit to experimental data, i.e. a hyperbolic function. Only microscopic muscle models proposed a physical origin of the hyperbolic force-velocity relation. However, microscopic muscle models can neither be used in simulation studies of complex human movements, nor as a blueprint for the construction of artificial muscles. A different macroscopic model predicted the hyperbolic force-velocity relation from an arrangement of three macroscopic physical components: a mechanical energy source (active element AE), a parallel damper element (PDE), and a serial element (SE) that exhibits operating points with hyperbolic force-velocity dependency. To verify the contraction dynamics of this model, the analytical model was compared to a numerical simulation and a hardware implementation. The analytical model only predicts the operating points at steady state, whereas the numerical model includes the dynamics of the contraction, and the hardware implementation is used to verify the real world functionality of the concept. The same experiments as usually performed with biological muscles were conducted, i.e. quick release experiments against different loads. A similar hyperbolic force-velocity relation was found in the numerical model and the hardware implementation. However, deviations from the analytical prediction were found. To resolve these discrepancies, two types of quick release experiments were performed. These experiments represent two extreme cases of the contraction dynamics, i.e. against a constant force (isotonic) and against an inertial mass. Both experiments revealed hyperbolic force-velocity relations. Interestingly, the analytical model not only predicts these extreme cases, but additionally all contraction states in between as well. It was possible to validate these predictions with the numerical model and the hardware experiment. These results prove that the origin of the hyperbolic force-velocity relation can be mechanically explained on a macroscopic level by the dynamical interaction of three mechanical elements. Thus, the concept can be seen as a starting point for the development of muscle-like bionic actuators. With these studies, this thesis contributes to the understanding of the role that muscles play in the control of periodic movements, and proposes a design concept allowing a transfer of their beneficial properties into technical systems. By using information theory to quantify the control effort, technical biological systems can be compared and key characteristics can be identified. These new insights and methods contribute to the integrated view of biological movement generation.
Open Access
Four considerations on interdisciplinary learning at the boundaries of human and engineering sciences
(2022) Beckerle, Philipp; Hao, Chenxu; Häufle, Daniel F. B.; Russwinkel, Nele
Open Access
A geometry- and muscle-based control architecture for synthesising biological movement
(2021) Walter, Johannes R.; Günther, Michael; Häufle, Daniel F. B.; Schmitt, Syn
A key problem for biological motor control is to establish a link between an idea of a movement and the generation of a set of muscle-stimulating signals that lead to the movement execution. The number of signals to generate is thereby larger than the body’s mechanical degrees of freedom in which the idea of the movement may be easily expressed, as the movement is actually executed in this space. A mathematical formulation that provides a solving link is presented in this paper in the form of a layered, hierarchical control architecture. It is meant to synthesise a wide range of complex three-dimensional muscle-driven movements. The control architecture consists of a ‘conceptional layer’, where the movement is planned, a ‘structural layer’, where the muscles are stimulated, and between both an additional ‘transformational layer’, where the muscle-joint redundancy is resolved. We demonstrate the operativeness by simulating human stance and squatting in a three-dimensional digital human model (DHM). The DHM considers 20 angular DoFs and 36 Hill-type muscle-tendon units (MTUs) and is exposed to gravity, while its feet contact the ground via reversible stick-slip interactions. The control architecture continuously stimulates all MTUs (‘structural layer’) based on a high-level, torque-based task formulation within its ‘conceptional layer’. Desired states of joint angles (postural plan) are fed to two mid-level joint controllers in the ‘transformational layer’. The ‘transformational layer’ communicates with the biophysical structures in the ‘structural layer’ by providing direct MTU stimulation contributions and further input signals for low-level MTU controllers. Thereby, the redundancy of the MTU stimulations with respect to the joint angles is resolved, i.e. a link between plan and execution is established, by exploiting some properties of the biophysical structures modelled. The resulting joint torques generated by the MTUs via their moment arms are fed back to the conceptional layer, closing the high-level control loop. Within our mathematical formulations of the Jacobian matrix-based layer transformations, we identify the crucial information for the redundancy solution to be the muscle moment arms, the stiffness relations of muscle and tendon tissue within the muscle model, and the length-stimulation relation of the muscle activation dynamics. The present control architecture allows the straightforward feeding of conceptional movement task formulations to MTUs. With this approach, the problem of movement planning is eased, as solely the mechanical system has to be considered in the conceptional plan.
Open Access
Implementation and validation of the extended Hill-type muscle model with robust routing capabilities in LS-DYNA for active human body models
(2017) Kleinbach, Christian; Martynenko, Oleksandr; Promies, Janik; Häufle, Daniel F. B.; Fehr, Jörg; Schmitt, Syn
In the state of the art finite element AHBMs for car crash analysis in the LS-DYNA software material named *MAT_MUSCLE (*MAT_156) is used for active muscles modeling. It has three elements in parallel configuration, which has several major drawbacks: restraint approximation of the physical reality, complicated parameterization and absence of the integrated activation dynamics. This study presents implementation of the extended four element Hill-type muscle model with serial damping and eccentric force-velocity relation including Ca2+ dependent activation dynamics and internal method for physiological muscle routing.
Open Access
Muscle preflex response to perturbations in locomotion : in vitro experiments and simulations with realistic boundary conditions
(2023) Araz, Matthew; Weidner, Sven; Izzi, Fabio; Badri-Spröwitz, Alexander; Siebert, Tobias; Häufle, Daniel F. B.
Neuromuscular control loops feature substantial communication delays, but mammals run robustly even in the most adverse conditions. In vivo experiments and computer simulation results suggest that muscles’ preflex - an immediate mechanical response to a perturbation - could be the critical contributor. Muscle preflexes act within a few milliseconds, an order of magnitude faster than neural reflexes. Their short-lasting action makes mechanical preflexes hard to quantify in vivo. Muscle models, on the other hand, require further improvement of their prediction accuracy during the non-standard conditions of perturbed locomotion. Our study aims to quantify the mechanical work done by muscles during the preflex phase (preflex work) and test their mechanical force modulation. We performed in vitro experiments with biological muscle fibers under physiological boundary conditions, which we determined in computer simulations of perturbed hopping. Our findings show that muscles initially resist impacts with a stereotypical stiffness response - identified as short-range stiffness - regardless of the exact perturbation condition. We then observe a velocity adaptation to the force related to the amount of perturbation similar to a damping response. The main contributor to the preflex work modulation is not the change in force due to a change in fiber stretch velocity (fiber damping characteristics) but the change in magnitude of the stretch due to the leg dynamics in the perturbed conditions. Our results confirm previous findings that muscle stiffness is activity-dependent and show that also damping characteristics are activity-dependent. These results indicate that neural control could tune the preflex properties of muscles in expectation of ground conditions leading to previously inexplicable neuromuscular adaptation speeds.
Open Access
Muscle prestimulation tunes velocity preflex in simulated perturbed hopping
(2023) Izzi, Fabio; Mo, An; Schmitt, Syn; Badri-Spröwitz, Alexander; Häufle, Daniel F. B.
Muscle fibres possess unique visco-elastic properties, which generate a stabilising zero-delay response to unexpected perturbations. This instantaneous response - termed “preflex” - mitigates neuro-transmission delays, which are hazardous during fast locomotion due to the short stance duration. While the elastic contribution to preflexes has been studied extensively, the function of fibre viscosity due to the force-velocity relation remains unknown. In this study, we present a novel approach to isolate and quantify the preflex force produced by the force-velocity relation in musculo-skeletal computer simulations. We used our approach to analyse the muscle response to ground-level perturbations in simulated vertical hopping. Our analysis focused on the preflex-phase - the first 30 ms after impact - where neuronal delays render a controlled response impossible. We found that muscle force at impact and dissipated energy increase with perturbation height, helping reject the perturbations. However, the muscle fibres reject only 15% of step-down perturbation energy with constant stimulation. An open-loop rising stimulation, observed in locomotion experiments, amplified the regulatory effects of the muscle fibre’s force–velocity relation, resulting in 68% perturbation energy rejection. We conclude that open-loop neuronal tuning of muscle activity around impact allows for adequate feed-forward tuning of muscle fibre viscous capacity, facilitating energy adjustment to unexpected ground-level perturbations.
Open Access
Optimality principles in human point-to-manifold reaching accounting for muscle dynamics
(2020) Wochner, Isabell; Driess, Danny; Zimmermann, Heiko; Häufle, Daniel F. B.; Toussaint, Marc; Schmitt, Syn
Human arm movements are highly stereotypical under a large variety of experimental conditions. This is striking due to the high redundancy of the human musculoskeletal system, which in principle allows many possible trajectories toward a goal. Many researchers hypothesize that through evolution, learning, and adaption, the human system has developed optimal control strategies to select between these possibilities. Various optimality principles were proposed in the literature that reproduce human-like trajectories in certain conditions. However, these studies often focus on a single cost function and use simple torque-driven models of motion generation, which are not consistent with human muscle-actuated motion. The underlying structure of our human system, with the use of muscle dynamics in interaction with the control principles, might have a significant influence on what optimality principles best model human motion. To investigate this hypothesis, we consider a point-to-manifold reaching task that leaves the target underdetermined. Given hypothesized motion objectives, the control input is generated using Bayesian optimization, which is a machine learning based method that trades-off exploitation and exploration. Using numerical simulations with Hill-type muscles, we show that a combination of optimality principles best predicts human point-to-manifold reaching when accounting for the muscle dynamics.
Open Access
Slack-based tunable damping leads to a trade-off between robustness and efficiency in legged locomotion
(2023) Mo, An; Izzi, Fabio; Gönen, Emre Cemal; Häufle, Daniel F. B.; Badri-Spröwitz, Alexander
Animals run robustly in diverse terrain. This locomotion robustness is puzzling because axon conduction velocity is limited to a few tens of meters per second. If reflex loops deliver sensory information with significant delays, one would expect a destabilizing effect on sensorimotor control. Hence, an alternative explanation describes a hierarchical structure of low-level adaptive mechanics and high-level sensorimotor control to help mitigate the effects of transmission delays. Motivated by the concept of an adaptive mechanism triggering an immediate response, we developed a tunable physical damper system. Our mechanism combines a tendon with adjustable slackness connected to a physical damper. The slack damper allows adjustment of damping force, onset timing, effective stroke, and energy dissipation. We characterize the slack damper mechanism mounted to a legged robot controlled in open-loop mode. The robot hops vertically and planarly over varying terrains and perturbations. During forward hopping, slack-based damping improves faster perturbation recovery (up to 170%) at higher energetic cost (27%). The tunable slack mechanism auto-engages the damper during perturbations, leading to a perturbation-trigger damping, improving robustness at a minimum energetic cost. With the results from the slack damper mechanism, we propose a new functional interpretation of animals’ redundant muscle tendons as tunable dampers.
Open Access
Theoretical hill-type muscle and stability : numerical model and application
(2013) Schmitt, Syn; Günther, Michael; Rupp, Tille; Bayer, Alexandra; Häufle, Daniel F. B.
The construction of artificial muscles is one of the most challenging developments in today's biomedical science. The application of artificial muscles is focused both on the construction of orthotics and prosthetics for rehabilitation and prevention purposes and on building humanoid walking machines for robotics research. Research in biomechanics tries to explain the functioning and design of real biological muscles and therefore lays the fundament for the development of functional artificial muscles. Recently, the hyperbolic Hill-type force-velocity relation was derived from simple mechanical components. In this contribution, this theoretical yet biomechanical model is transferred to a numerical model and applied for presenting a proof-of-concept of a functional artificial muscle. Additionally, this validated theoretical model is used to determine force-velocity relations of different animal species that are based on the literature data from biological experiments. Moreover, it is shown that an antagonistic muscle actuator can help in stabilising a single inverted pendulum model in favour of a control approach using a linear torque generator.