Browsing by Author "Schmitt, Syn (Prof. Dr. rer. nat.)"

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Open Access
Biophysical validity of reduced soft tissue modelling in neuro-musculoskeletal simulations
(Stuttgart : Institut für Modellierung und Simulation Biomechanischer Systeme, Computational Biophysics and Biorobotics, 2024) Hammer, Maria; Schmitt, Syn (Prof. Dr. rer. nat.)
In the past decades, neuro-musculoskeletal simulations have become a key technology in biomechanical research, and are increasingly utilised to support clinical decision-making processes, evaluate occupational safety, and facilitate the design of assistive devices. The importance of precise and physiologically valid simulations cannot be emphasised enough across all application fields. However, achieving this accuracy becomes particularly challenging when developing reduced descriptions of soft tissue compartments, where the degrees of freedom and structural complexity are condensed into predominantly phenomenological or homogenised sub-models. Furthermore, it necessitates a deep understanding of the dynamic interplay among different soft tissue elements in the body, which, in turn, requires a high level of reliability and confidence in the employed underlying model. In order to ensure the usefulness of the models, it is crucial to strike a balance between the level of detail and the limitations arising from simplifications. This involves considering various possibilities to validate the mechanical behaviour of each sub-model individually and the overall model as a whole. The scientific aim of this dissertation is to investigate the load sharing of soft tissue compartments at the example of the human lumbar spine during active motions by using predictive simulations. To set the basis for this kind of research, the main objective is to create, calibrate, verify and validate a detailed neuro-musculoskeletal model, which gives rise to three research questions that guide this thesis: (1) How can (and should) common approaches for reduced single tissue models be improved to increase the level of biomechanical validity and physical verification of both the sub-models themselves, and the multibody models composed of them? (2) Which sub-structures are of biomechanical relevance for estimating internal forces and torques on a full-body scale? (3) Which validation methods need to be considered during the development of a physiological spine model, and how can the corresponding simulation results be assessed? This thesis encompasses five journal articles studies, contributing to the different aspects of the three research questions. More precisely, Contribution I addresses research questions (1) and (3) regarding how to enhance biomechanical validity of muscle routing in multibody models by introducing a novel algorithm for redirecting muscle paths. With this method, the physiological accuracy of muscle length and moment arm representations within Hill-type models can be refined, particularly for muscles spanning multiple joints with multiple degrees of freedom. Contribution II focuses on the intuitive assessment of the relative motion between two vertebral bodies. Using a newly developed method for graphical representation of finite helical axes, which fully encapsulates the information about rotation and translation of the relative motion between two vertebral bodies, extensive data sets were effectively presented through clustering methods. This work, thereby, contributes to research question (3) since the finite helical axis can serve as measure for model validation. Contribution III presents a comprehensive simulation study and introduces a detailed generic model of the human thoracolumbar spine. This generic model includes several hundred muscle and ligament strands, along with intervertebral joints modelled as free joints constrained only by intervertebral discs. Notably, the model is able to balance gravity in an upright position without additional constraints and with only a physiologically low level of muscle stimulation. The description of model development and validation significantly contributes to research question (3). Moreover, the analysis of load sharing among the three soft tissue sub-structures, namely ligaments, muscles, and intervertebral discs, revealed an almost equal distribution of bending moment during forward flexion, offering insights for research question (2). Additionally, this paper introduces a workflow for geometric individualisation of the generic model based on landmark data obtained from computed-tomography scans. The investigation of subject-specific forces and torques exhibits significant inter- and intrapersonal differences in the lumbar load distribution. These findings deepen the biomechanical understanding of complex interactions within the spine. Contribution IV explores the influence of neglecting entire passive tissue groups, precisely intervertebral discs and ligaments, which is common practice in many spine models. Using an inverse dynamic approach, this study contributes to research questions (2) and (3) by providing cross-platform validation. The examination of kinematic models that exclude ligament and intervertebral disc tissues reveals a tendency for highly overestimated muscle forces. These findings highlight the importance of considering all relevant soft tissue structures in computational models to ensure accurate muscle force estimations. Lastly, the Contribution V directly addresses research question (1) by tackling the challenge of incorporating energy conservation in surrogate models representing the elastic mechanical responses of intervertebral discs. It introduces a novel approach that surpasses currently used elastic models in terms of precision, coupling of different degrees of freedom, and nonlinear behaviour. This advancement increases the accuracy and physical validity while also enabling the individualisation of the mechanical behaviour of subject- and level-specific intervertebral disc geometry. In order to achieve the aforementioned aims and answer the research questions, a multibody simulation framework has been extended by the novel algorithms developed within the scope of this thesis. These algorithms improve the geometric quality of soft tissue representations and refine accuracy of predicted internal forces and torques while preserving basic physical principles. Furthermore, a pre-processor typically used to scale population-based models has been modified to serve two additional purposes. On the one hand, the existing code was advanced to create geometrically individualised models based on landmark positions derived from computed-tomography scans. On the other hand, the functionality to generate models compatible with another widely used multibody simulation tool was included. Having identical models facilitates cross-platform validation, and allows to test muscle, ligament and intervertebral disc sub-models, and whole thoracolumbar spine models in different scenarios. In summary, this thesis enhances existing methods and provides new approaches to create more accurate neuro-musculoskeletal models capable of predicting internal forces and kinematics. The detailed spine model developed during this thesis serves as a valuable foundation for future investigations, including subject-specific, non-invasive implant testing, and exploration of the rotation axes in complex movements and post-surgical scenarios.
Open Access
From muscle spindle to spinal cord : a modelling approach of the hierarchical organization in sensorimotor control
(Stuttgart : Institut für Modellierung und Simulation Biomechanischer Systeme, Computational Biophysics and Biorobotics, 2025) Santana Chacon, Pablo Filipe; Schmitt, Syn (Prof. Dr. rer. nat.)
The muscle spindle is an essential proprioceptor, significantly involved in sensing limb position and movement. Although biological spindle models exist for years, the gold-standard for motor control in biomechanics are still sensors built of homogenized spindle output models due to their simpler combination with neuro-musculoskeletal models. The performance of new studies that consider different structures of the hierarchical sensorimotor control system, implementing physiologically-motivated neuromechanical models aligned to proprioception, is essential to enable a more holistic understanding about movement. The incorporation of more biological proprioceptive and neuronal circuit models to muscles can make neuro-musculoskeletal systems more appropriate to investigate and elucidate motor control. Therefore, initially, this doctoral dissertation presents a more physiological model of the muscle spindle that considers the individual characteristics of involved tissue compartments, aligned to the advantage of easy integration into large-scale musculoskeletal models. Different stretches in the intrafusal fibers were simulated in the model's variations following the spindle afferent recorded in previous experiments in feline soleus muscle. Additionally, the proposed enhanced Hill-type spindle models had their parameters extensively optimized to match the experimental conditions, and the resulting model was validated against data from rats’ triceps surae muscle. As result, the model exhibits a stable and valid prediction of experimentally observed muscle spindle responses. At the same time, it presents a well-tuned Hill-type model as muscle spindle fibers – accounting for real sarcomere force-length and force-velocity aspects - and its activation dynamics is similar to the one applied to Hill-type model for extrafusal fibers, making it more easily integrated in multi-body simulations. Furthermore, this dissertation aims to demonstrate that the afferent firings from the muscle spindle model can be processed by neuronal networks and are important for motor control. Hence, the spindle model was integrated to a previous implemented extrafusal fiber model, inside of the demoa multi-body simulation framework. This structure composed by extrafusal (muscle) and intrafusal (spindle) fibers replaced the muscle-tendon units (MTUs) of a prior developed arm model composed by two degrees of freedom and six MTUs, into the same simulation framework. Additionally, a spinal cord model, based on literature, was implemented in the Nest spiking neural network simulator. The spinal network has 6 neurons per muscle - alpha, dynamic gamma and static gamma motoneurons, together with Ia, propriospinal and Renshaw interneurons – and their respective physiological connections. The coupling between demoa and Nest simulators was implemented using a Cython interface. The spinal cord network - in its two variations of complete and simpler circuitry (including only Renshaw pathway, without spindle proprioception) - had its synaptic weights optimized to perform a center-out reaching task using the musculoskeletal model, without and with perturbation (increment of lower arm segment in 1 kg). As result, the complete spinal cord circuitry learned how to successfully reach all the evaluated targets without and with perturbation, demonstrating the sensorimotor control learning in the environment formed from muscle spindle to spinal circuitry, encompassing the two simulators. On the other hand, the simpler spinal cord circuitry did not succeed in the task of reach all the targets, also demonstrating reduced performance with perturbation. Moreover, the spindle afferent synapses in the complete circuitry were intensified for the higher targets (considered more difficult under gravity) when comparing the scenarios without and with perturbation. Therefore, the muscle spindle connections were strengthened for difficult targets under perturbation, highlighting the importance of spindle proprioception in these more difficult scenarios, as well as indicated by the circuitry that does not consider proprioception and did not show a similar successful performance. Finally, this dissertation offers a novel possibility of neuro-musculoskeletal modelling environment formed with demoa and Nest simulators. Future outlook includes the integration of the musculoskeletal and spinal cord models with higher-level models of Central Nervous System, aligned to further sophisticated details of the current modelling, to allow a more comprehensive understanding of sensorimotor behavior.
Open Access
Über die Regelung muskelgetriebener Systeme : ein hierarchischer und geometriebasierter Ansatz
(Stuttgart : Institut für Modellierung und Simulation Biomechanischer Systeme, Computational Biophysics and Biorobotics, 2022) Walter, Johannes R.; Schmitt, Syn (Prof. Dr. rer. nat.)
Computersimulationen sind heutzutage eine leistungsfähige wissenschaftliche Methode um Hypothesen unter simulierten Bedingungen zu überprüfen. Dennoch scheinen biologische Bewegungen von mehrgelenkigen Systemen mit einer Vielzahl von Muskeln das Ergebnis von neuronalen Kommandos zu sein, die zu komplex sind um algorithmisch implementiert zu werden. Daher ist die Vielfalt, sowie die Komplexität von in-silico synthetisierten, muskelgetriebenen Bewegungen noch immer gering. Ein Schlüsselproblem zur Regelung biologischer Bewegung ist es eine Verbindung zwischen einer konzeptionellen Idee der Bewegung und der Bereitstellung von Muskelstimulationen herzustellen. Dies kann sich als schwierig erweisen, da in biologischen Bewegungen die Anzahl der Muskeln größer ist als die Dimension des konzeptionellen Raums der Bewegungsidee, bspw. der mechanischen Freiheitsgraden (FHG) des Skelettsystems. In dieser Dissertation wird eine mathematische Formulierung einer hierarchischen Regelungsarchitektur vorgestellt, die eine solche Verbindung herstellt und die dazu ausgelegt ist eine Vielzahl von dreidimensionalen, muskelgetriebenen Bewegungen zu synthetisieren. Die Funktionsfähigkeit der Regelungsarchitektur ist anhand von verschiedenen menschlichen Bewegungsaufgaben demonstriert. Dies beinhaltet Simulationen von einem aufrechtem Stand, von einer Einstiegsbewegung in ein Fahrzeug, um ergonomische Rückschlüsse von einer virtuellen Designänderung zu ziehen, und von einem Sturz in eine Badewanne, um die Aufklärung eines Kriminalfalles zu unterstützen. Das zur Bewegungssynthese verwendete dreidimensionale digitale Menschmodell (DMM) besteht aus 20 Gelenk FHG und 36 Hill-Typ Muskel-Sehnen Einheiten (MSE). Das DMM ist erdähnlicher Gravitation ausgesetzt und die Füße interagieren mit dem Boden durch reversible Haft- und Gleitreibungskontakte. Die Regelungsarchitektur liefert kontinuierliche Stimulationen für alle MSE, basierend auf einer konzeptionellen Formulierung der Bewegungsaufgabe in den Koordinaten der Gelenkwinkel, der Gelenkmomente, der Positionen der Gliedmaßen oder in anderen konzeptionellen Koordinaten. Die Hierarchie der Regelungsarchitektur besteht aus drei Ebenen, der 'Konzeptionsebene', der 'Transformationsebene' und der 'Strukturebene'. In der 'Konzeptionsebene' wird die Bewegungsaufgabe in den konzeptionellen Koordinaten der Winkel, der Momente oder der Positionen formuliert und geregelt. Die Ausgangsgröße des konzeptionellen Reglers wird in einen Bewegungsplan für die Gelenkwinkel transformiert und bildet die Eingangsgröße für zwei Gelenkwinkelregler in der 'Transformationsebene'. Die 'Transformationsebene' kommuniziert mit den biologischen Strukturen in der 'Strukturebene', indem sie zum einen direkte Stimulationen für die MSE bereitstellt und zum anderen weitere Eingangssignale für strukturelle MSE Regler liefert. Dabei wird die Redundanz zwischen den MSE Stimulationen und den Gelenkwinkeln aufgelöst. Hierzu werden die Charakteristiken der modellierten biophysikalischen Strukturen, die Hebelarme der Muskeln, die Steifigkeitsverhältnisse innerhalb des Muskelmodells und die Längen-Stimulationsabhängigkeit der Aktivierungsdynamik, zu Nutze gemacht. Die von den MSE über ihre Hebelarme generierten Gelenkmomente beschleunigen die Körpersegmente und, indem die konzeptionellen Koordinaten an die Regler in der 'Konzeptionsebene' zurückgeführt werden, wird der hierarchische Regelkreis geschlossen. Die präsentierte Regelungsarchitektur erlaubt es damit eine konzeptionelle Bewegungsaufgabe direkt in Stimulationssignale der MSE zu übersetzen. Mit diesem Ansatz wird das Problem der Bewegungsplanung erleichtert, da bspw. nur das mechanische System in der konzeptionellen Planung betrachtet werden muss. Da zudem die Auflösung der Muskel-Gelenk-Redundanz nicht eindeutig ist, verbleibt zur Regelung eine 'ungeregelte Mannigfaltigkeit', mit der die Kokontraktion aller Muskeln an dem selben Gelenk genau so angepasst werden kann, dass sie nicht mit der Erfüllung der Bewegungsaufgabe in Konflikt steht. Die Ergebnisse dieser Dissertation sind vielversprechend bezüglich der Anwendung der Regelungsarchitektur für die Synthese von dynamischen und komplexen muskelgetriebenen Bewegungen, auch für robotische Systeme die mit künstlichen Muskeln ausgestattet sind. Die internen Zustände des muskuloskelettalen Models sind zu weiterführenden Analysen geeignet, wie z.B. zur Evaluation der Ergonomie oder zur Abschätzung gesundheitlicher Auswirkungen der Bewegung.