Methods of system identification, parameter estimation and optimisation applied to problems of modelling and control in engineering and physiology

Mathematical and computer-based models provide the foundation of most methods of engineering design. They are recognised as being especially important in the development of integrated dynamic systems, such as “control-configured” aircraft or in complex robotics applications. These models usually involve combinations of linear or nonlinear ordinary differential equations or difference equations, partial differential equations and algebraic equations. In some cases models may be based on differential algebraic equations. Dynamic models are also important in many other fields of research, including physiology where the highly integrated nature of biological control systems is starting to be more fully understood. Although many models may be developed using physical, chemical, or biological principles in the initial stages, the use of experimentation is important for checking the significance of underlying assumptions or simplifications and also for estimating appropriate sets of parameters. This experimental approach to modelling is also of central importance in establishing the suitability, or otherwise, of a given model for an intended application – the so-called “model validation” problem. System identification, which is the broad term used to describe the processes of experimental modelling, is generally considered to be a mature field and classical methods of identification involve linear discrete-time models within a stochastic framework. The aspects of the research described in this thesis that relate to applications of identification, parameter estimation and optimisation techniques for model development and model validation mainly involve nonlinear continuous time models Experimentally-based models of this kind have been used very successfully in the course of the research described in this thesis very in two areas of physiological research and in a number of different engineering applications. In terms of optimisation problems, the design, experimental tuning and performance evaluation of nonlinear control systems has much in common with the use of optimisation techniques within the model development process and it is therefore helpful to consider these two areas together. The work described in the thesis is strongly applications oriented. Many similarities have been found in applying modelling and control techniques to problems arising in fields that appear very different. For example, the areas of neurophysiology, respiratory gas exchange processes, electro-optic sensor systems, helicopter flight-control, hydro-electric power generation and surface ship or underwater vehicles appear to have little in common. However, closer examination shows that they have many similarities in terms of the types of problem that are presented, both in modelling and in system design. In addition to nonlinear behaviour; most models of these systems involve significant uncertainties or require important simplifications if the model is to be used in a real-time application such as automatic control. One recurring theme, that is important both in the modelling work described and for control applications, is the additional insight that can be gained through the dual use of time-domain and frequency-domain information. One example of this is the importance of coherence information in establishing the existence of linear or nonlinear relationships between variables and this has proved to be valuable in the experimental investigation of neuromuscular systems and in the identification of helicopter models from flight test data. Frequency-domain techniques have also proved useful for the reduction of high-order multi-input multi-output models. Another important theme that has appeared both within the modelling applications and in research on nonlinear control system design methods, relates to the problems of optimisation in cases where the associated response surface has many local optima. Finding the global optimum in practical applications presents major difficulties and much emphasis has been placed on evolutionary methods of optimisation (both genetic algorithms and genetic programming) in providing usable methods for optimisation in design and in complex nonlinear modelling applications that do not involve real-time problems. Another topic, considered both in the context of system modelling and control, is parameter sensitivity analysis and it has been found that insight gained from sensitivity information can be of value not only in the development of system models (e.g. through investigation of model robustness and the design of appropriate test inputs), but also in feedback system design and in controller tuning. A technique has been developed based on sensitivity analysis for the semi-automatic tuning of cascade and feedback controllers for multi-input multi-output feedback control systems. This tuning technique has been applied successfully to several problems. Inverse systems also receive significant attention in the thesis. These systems have provided a basis for theoretical research in the control systems field over the past two decades and some significant applications have been reported, despite the inherent difficulties in the mathematical methods needed for the nonlinear case. Inverse simulation methods, developed initially by others for use in handling-qualities studies for fixed-wing aircraft and helicopters, are shown in the thesis to provide some important potential benefits in control applications compared with classical methods of inversion. New developments in terms of methodology are presented in terms of a novel sensitivity based approach to inverse simulation that has advantages in terms of numerical accuracy and a new search-based optimisation technique based on the Nelder-Mead algorithm that can handle inverse simulation problems involving hard nonlinearities. Engineering applications of inverse simulation are presented, some of which involve helicopter flight control applications while others are concerned with feed-forward controllers for ship steering systems. The methods of search-based optimisation show some important advantages over conventional gradient-based methods, especially in cases where saturation and other nonlinearities are significant. The final discussion section takes the form of a critical evaluation of results obtained using the chosen methods of system identification, parameter estimation and optimisation for the modelling and control applications considered. Areas of success are highlighted and situations are identified where currently available techniques have important limitations. The benefits of an inter-disciplinary and applications-oriented approach to problems of modelling and control are also discussed and the value in terms of cross-fertilisation of ideas resulting from involvement in a wide range of applications is emphasised. Areas for further research are discussed

Towards patient-specific modelling as a pre-operative planning strategy and follow up assessment for the treatment of advanced heart failure with rotary blood pumps

Background: Ventricular Assist Devices (VADs) insertion is an established treatment for patients with end-stage heart failure waiting for a heart transplant or in need for long-term circulatory support (destination therapy). Rotary blood pumps (RBP) are the most popular devices in view of their size and performance. Pre-operative planning strategy for the insertion of a left ventricular assist device (LVAD) requires a timely discussion at a Multi-Disciplinary Team Meeting (MDT). Clinical-decision making is based according to the needs of the patient and must be processed without delays. Nevertheless, thrombus formation remains a feared complication which affects outcome. VADs operate in a flow regime which is difficult to simulate: the transitional region at the boundary of laminar and turbulent flow (low Reynolds number). Different methods have been used but the best approach remains debatable. Computational Fluid Dynamics (CFD) is an attractive and invaluable tool for the study of the interactions between VADs and the cardiovascular system. The aim of this thesis is three-fold: a) to investigate the use of pressure-volume analysis in a clinical setting through the review of six heart failure patients previously discussed at a MDT meeting with a view to predict or guide further management; b) to review the theory behind modelling approaches to VADs and their interactions with the cardiovascular system for better understanding of their clinical use. Then, an overview of computational fluid dynamics (CFD) is considered as a prelude to its application to the analysis of VADs performance. Additionally, the development of a simplified model of centrifugal pump will be used in initial simulations as preliminary analysis; c) to examine an example of a proof-of-concept pilot patient-specific model of an axial flow pump (HeartMate II) as pre-operative planning strategy in a patient-specific model with a view to identify potential critical areas that may affect pump function and outcome in a clinical setting. Material and Methods: 3D reconstruction from CT-scan images of patients who underwent the insertion of rotary blood pumps, namely HeartWare HVAD and HeartMate II. Ansys Fluent has been used for CFD analysis based on the fundamental governing equations of motion. Blood has been modelled as incompressible, Newtonian fluid with density = 1060 and viscosity = 0.0035 kg/m-s. The laminar and SST models have been used for comparison purposes. The rotational motion of the impeller has been implemented using the moving reference frame (MRF) approach. The sliding mesh method has also been used to account for unsteady interaction between stationary and moving part. The no-slip condition has been applied to all walls, which were assumed to be rigid. Boundary conditions consisting of velocity inlet and pressure outlet of the pump based on different settings and constant rotational speed for the impeller. Pressure-velocity coupling has been based on the coupled scheme. Spatial discretisation consisted of the “least square cell based” gradient for velocity and “PRESTO” or second order for pressure. Second order upwind has been set for the momentum, turbulent kinetic energy and specific dissipation rate. First order implicit has been set for transient formulation. The pseudo transient algorithm (steady state), the high order relaxation term and the warped-face gradient correction have been used to add an unsteady term to the solution equations with the aim to improve stability and enhance convergence. Specific settings have been considered for comparison purposes. Results: Pressure-volume simulation analysis in six advanced heart failure patients showed that an integrated model of the cardiovascular system based on lumped-parameter representation, modified time-varying elastance and pressure-volume analysis of ventricular function seems a feasible and suitable approach yielding a sufficiently accurate quantitative analysis in real time, therefore applicable within the time-constraints of a clinical setting. Lumped-parameter models consist of simultaneous ordinary differential equations complemented by an algebraic balance equation and are suitable for examination of global distribution of pressure, flow and volume over a range of physiological conditions with inclusion of the interaction between modelled components. Higher level lumped-parameter modelling is needed to address the interaction between the circulation and other systems based on a compromise between complexity and ability to set the required parameters to personalise an integrated lumped-parameter model for a patient-specific approach. CARDIOSIM© fulfils these requirements and does address the systems interaction with its modular approach and assembly of models with varying degree of complexity although 0-D and 1-D coupling may be required for the evaluation of long-term VAD support. The challenge remains the ability to predict outcome over a longer period of time. The preliminary CFD simulations with the HeartWare HVAD centrifugal pump demonstrated that it is possible to obtain an accurate analysis in a timely manner to complement the clinical review process. The simulations with the pilot patient-specific model of the HeartMate II axial flow pump revealed that a complex 3D reconstruction is feasible in a timely manner and can be used to generate sufficiently accurate results to be used in the context of a MDT meeting for the purposes of clinical decision-making. Overall, these three studies demonstrate that the time frame of the simulations was within hours which may fit the time constraints of the clinical environment in the context of a MDT meeting. More specifically, it was shown that the laminar model may be used for an initial evaluation of the flow development within the pump. Nonetheless, the k- model offers higher accuracy if the timeline of the clinical setting allows for a longer simulation. Conclusion: This thesis aimed at the understanding of the use of computational modelling as a pre-operative planning strategy and follow up assessment for the treatment of advanced heart failure with rotary blood pumps. The novelty lays in the use of both pressure-volume simulation analysis and 3D flow dynamics studies in VADs with a view to treatment optimisation and outcome prediction within the time constraints of a clinical setting in the context of a MDT meeting. The clinical significance and the contribution to the field is a more targeted approach for different groups of patients and a more quantitative evaluation in the clinical decision process based on a pro-active co-operation between clinicians and scientists reducing the potential for “guess work”. The results of this thesis are a proof-of-concept as a prelude to a potential future implementation of patient-specific modelling within a clinical setting on a daily basis demonstrating a clear clinical significance and contribution to the field. The proposed approach does not consider modelling and simulation as a substitute for clinical experience but an additional tool to guide therapeutic intervention and complement the clinical decision process in which the clinician remains the ultimate decision-maker. Such an approach may well add a different dimension to the problem of heart failure with potential for high return in terms of patient’s outcome and long-term surveillance. The same principles would be applicable to other cardiovascular problems in line with the current concept of “Team Approach” such as the Heart Team, the Structural Heart Team or the Aortic Team. The present work has taken this concept closer to clinical delivery and has highlighted its potential but further work remains to be done in refining the technique.Background: Ventricular Assist Devices (VADs) insertion is an established treatment for patients with end-stage heart failure waiting for a heart transplant or in need for long-term circulatory support (destination therapy). Rotary blood pumps (RBP) are the most popular devices in view of their size and performance. Pre-operative planning strategy for the insertion of a left ventricular assist device (LVAD) requires a timely discussion at a Multi-Disciplinary Team Meeting (MDT). Clinical-decision making is based according to the needs of the patient and must be processed without delays. Nevertheless, thrombus formation remains a feared complication which affects outcome. VADs operate in a flow regime which is difficult to simulate: the transitional region at the boundary of laminar and turbulent flow (low Reynolds number). Different methods have been used but the best approach remains debatable. Computational Fluid Dynamics (CFD) is an attractive and invaluable tool for the study of the interactions between VADs and the cardiovascular system. The aim of this thesis is three-fold: a) to investigate the use of pressure-volume analysis in a clinical setting through the review of six heart failure patients previously discussed at a MDT meeting with a view to predict or guide further management; b) to review the theory behind modelling approaches to VADs and their interactions with the cardiovascular system for better understanding of their clinical use. Then, an overview of computational fluid dynamics (CFD) is considered as a prelude to its application to the analysis of VADs performance. Additionally, the development of a simplified model of centrifugal pump will be used in initial simulations as preliminary analysis; c) to examine an example of a proof-of-concept pilot patient-specific model of an axial flow pump (HeartMate II) as pre-operative planning strategy in a patient-specific model with a view to identify potential critical areas that may affect pump function and outcome in a clinical setting. Material and Methods: 3D reconstruction from CT-scan images of patients who underwent the insertion of rotary blood pumps, namely HeartWare HVAD and HeartMate II. Ansys Fluent has been used for CFD analysis based on the fundamental governing equations of motion. Blood has been modelled as incompressible, Newtonian fluid with density = 1060 and viscosity = 0.0035 kg/m-s. The laminar and SST models have been used for comparison purposes. The rotational motion of the impeller has been implemented using the moving reference frame (MRF) approach. The sliding mesh method has also been used to account for unsteady interaction between stationary and moving part. The no-slip condition has been applied to all walls, which were assumed to be rigid. Boundary conditions consisting of velocity inlet and pressure outlet of the pump based on different settings and constant rotational speed for the impeller. Pressure-velocity coupling has been based on the coupled scheme. Spatial discretisation consisted of the “least square cell based” gradient for velocity and “PRESTO” or second order for pressure. Second order upwind has been set for the momentum, turbulent kinetic energy and specific dissipation rate. First order implicit has been set for transient formulation. The pseudo transient algorithm (steady state), the high order relaxation term and the warped-face gradient correction have been used to add an unsteady term to the solution equations with the aim to improve stability and enhance convergence. Specific settings have been considered for comparison purposes. Results: Pressure-volume simulation analysis in six advanced heart failure patients showed that an integrated model of the cardiovascular system based on lumped-parameter representation, modified time-varying elastance and pressure-volume analysis of ventricular function seems a feasible and suitable approach yielding a sufficiently accurate quantitative analysis in real time, therefore applicable within the time-constraints of a clinical setting. Lumped-parameter models consist of simultaneous ordinary differential equations complemented by an algebraic balance equation and are suitable for examination of global distribution of pressure, flow and volume over a range of physiological conditions with inclusion of the interaction between modelled components. Higher level lumped-parameter modelling is needed to address the interaction between the circulation and other systems based on a compromise between complexity and ability to set the required parameters to personalise an integrated lumped-parameter model for a patient-specific approach. CARDIOSIM© fulfils these requirements and does address the systems interaction with its modular approach and assembly of models with varying degree of complexity although 0-D and 1-D coupling may be required for the evaluation of long-term VAD support. The challenge remains the ability to predict outcome over a longer period of time. The preliminary CFD simulations with the HeartWare HVAD centrifugal pump demonstrated that it is possible to obtain an accurate analysis in a timely manner to complement the clinical review process. The simulations with the pilot patient-specific model of the HeartMate II axial flow pump revealed that a complex 3D reconstruction is feasible in a timely manner and can be used to generate sufficiently accurate results to be used in the context of a MDT meeting for the purposes of clinical decision-making. Overall, these three studies demonstrate that the time frame of the simulations was within hours which may fit the time constraints of the clinical environment in the context of a MDT meeting. More specifically, it was shown that the laminar model may be used for an initial evaluation of the flow development within the pump. Nonetheless, the k- model offers higher accuracy if the timeline of the clinical setting allows for a longer simulation. Conclusion: This thesis aimed at the understanding of the use of computational modelling as a pre-operative planning strategy and follow up assessment for the treatment of advanced heart failure with rotary blood pumps. The novelty lays in the use of both pressure-volume simulation analysis and 3D flow dynamics studies in VADs with a view to treatment optimisation and outcome prediction within the time constraints of a clinical setting in the context of a MDT meeting. The clinical significance and the contribution to the field is a more targeted approach for different groups of patients and a more quantitative evaluation in the clinical decision process based on a pro-active co-operation between clinicians and scientists reducing the potential for “guess work”. The results of this thesis are a proof-of-concept as a prelude to a potential future implementation of patient-specific modelling within a clinical setting on a daily basis demonstrating a clear clinical significance and contribution to the field. The proposed approach does not consider modelling and simulation as a substitute for clinical experience but an additional tool to guide therapeutic intervention and complement the clinical decision process in which the clinician remains the ultimate decision-maker. Such an approach may well add a different dimension to the problem of heart failure with potential for high return in terms of patient’s outcome and long-term surveillance. The same principles would be applicable to other cardiovascular problems in line with the current concept of “Team Approach” such as the Heart Team, the Structural Heart Team or the Aortic Team. The present work has taken this concept closer to clinical delivery and has highlighted its potential but further work remains to be done in refining the technique

Physiology-based Mathematical Models for the Intensive Care Unit: Application to Mechanical Ventilation

This work takes us a step closer to realizing personalized medicine, complementing empirical and heuristic way in which clinicians typically work. This thesis presents mechanistic models of physiology. These models, given continuous signals from a patient, can be fine-tuned via parameter estimation methods so that the model's outputs match the patient's. We thus obtain a virtual patient mimicking the patient at hand. Therapeutic scenarios can then be applied and optimal diagnosis and therapy can thus be attained. As such, personalized medicine can then be achieved without resorting to costly genetics. In particular we have developed a novel comprehensive mathematical model of the cardiopulmonary system that includes cardiovascular circulation, respiratory mechanics, tissue and alveolar gas exchange, as well as short-term neural control. Validity of the model was proven by the excellent agreement with real patient data, under normo-physiological as well as hypercapnic and hypoxic conditions, taken from literature. As a concrete example, a submodel of the lung mechanics was fine-tuned using real patient data and personalized respiratory parameters (resistance, R_rs, and compliance, C_rs) were estimated continually. This allows us to compute the patient's effort (Work of Breathing), continuously and more importantly noninvasively. Finally, the use of Bayesian estimation techniques, which allow incorporation of population studies and prior information about model's parameters, was proposed in the contest of patient-specific physiological models. A Bayesian Maximum a Posteriori Probability (MAP) estimator was implemented and applied to a case-study of respiratory mechanics. Its superiority against the classical Least Squares method was proven in data-poor conditions using both simulated and real animal data. This thesis can serve as a platform for a plethora of applications for cardiopulmonary personalized medicine

Index to NASA Tech Briefs, 1975

This index contains abstracts and four indexes--subject, personal author, originating Center, and Tech Brief number--for 1975 Tech Briefs

A Multi-Scale Approach to Airway Hyperresponsiveness: From Molecule to Organ

Airway hyperresponsiveness (AHR), a characteristic of asthma that involves an excessive reduction in airway caliber, is a complex mechanism reflecting multiple processes that manifest over a large range of length and time scales. At one extreme, molecular interactions determine the force generated by airway smooth muscle (ASM). At the other, the spatially distributed constriction of the branching airways leads to breathing difficulties. Similarly, asthma therapies act at the molecular scale while clinical outcomes are determined by lung function. These extremes are linked by events operating over intermediate scales of length and time. Thus, AHR is an emergent phenomenon that limits our understanding of asthma and confounds the interpretation of studies that address physiological mechanisms over a limited range of scales. A solution is a modular computational model that integrates experimental and mathematical data from multiple scales. This includes, at the molecular scale, kinetics, and force production of actin-myosin contractile proteins during cross-bridge and latch-state cycling; at the cellular scale, Ca2+ signaling mechanisms that regulate ASM force production; at the tissue scale, forces acting between contracting ASM and opposing viscoelastic tissue that determine airway narrowing; at the organ scale, the topographic distribution of ASM contraction dynamics that determine mechanical impedance of the lung. At each scale, models are constructed with iterations between theory and experimentation to identify the parameters that link adjacent scales. This modular model establishes algorithms for modeling over a wide range of scales and provides a framework for the inclusion of other responses such as inflammation or therapeutic regimes. The goal is to develop this lung model so that it can make predictions about bronchoconstriction and identify the pathophysiologic mechanisms having the greatest impact on AHR and its therapy

Aerospace Medicine and Biology: A continuing supplement 180, May 1978

This special bibliography lists 201 reports, articles, and other documents introduced into the NASA scientific and technical information system in April 1978

Adaptive Closed-Loop Neuromorphic Controller for Use in Respiratory Pacing

Respiratory pacing can treat ventilatory insufficiency through electrical stimulation of the respiratory muscles, or the respective innervating nerves, to induce ventilation. It avoids some of the adverse effects associated with mechanical ventilation such as risk of diaphragm atrophy and lung damage. However, current respiratory pacing systems provide stimulation in an open-loop manner. This often requires users to undergo frequent tuning sessions with trained clinicians if the specified stimulation parameters are unable to induce sufficient ventilation in the presence of time-varying changes in muscle properties, chest biomechanics, and metabolic demand. Lack of adaptation to these changes may lead to complications arising from hyperventilation or hypoventilation. A novel adaptive closed-loop neuromorphic controller for respiratory pacing has been developed to address the need for closed-loop control respiratory pacing capable of responding to changes in metabolic production of CO2, diaphragm muscle health, and biomechanics. A 3-stage processes was utilized to develop the controller. First, an adaptive controller that could follow a preset within-breath volume profile was developed in silico and evaluated in vivo in anesthetized rats with an intact spinal cord or with diaphragm hemiparesis induced by spinal cord hemisection. Second, a neuromorphic computational model was developed to generate a desired trajectory that reflects changes in breath volume and respiratory rate in response to arterial CO2 levels. An enhanced controller capable of generating and matching this model-based desired trajectory was evaluated in silico and in vivo on rats with depressed ventilation and diaphragm hemiparesis. Finally, the enhanced adaptive controller was modified for human-related biomechanics and CO2 dynamics and evaluated in silico under changes of metabolic demand, presence of muscle fatigue, and after randomization of model parameters to reproduce expected between-subject differences. Results showed that the adaptive controller could adapt and modulate stimulation parameters and respiratory rate to follow a desired model-generated breath volume trajectory in response to dynamic arterial CO2 levels. In silico studies aimed at assessing potential for clinical translation showed that an enhanced controller modified for human use could successfully control ventilation to achieve and maintain normocapnic arterial CO2 levels. Overall, these results suggest that use of an adaptive closed-loop controller could lead to improved ventilatory outcomes and quality of life for users of adaptive respiratory pacing

Aerospace Medicine and Biology: A continuing bibliography with indexes (supplement 134)

This special bibliography lists 301 reports, articles, and other documents introduced into the NASA Scientific and Technical Information System in October 1974

Numerical Study of Laryngeal Control of Phonation using Realistic Finite Element Models of a Canine Larynx

While many may take it for granted, the human voice is an incredible feat. An average person can produce a great variety of voices and change voice characteristics agilely even without formal training. Last several decades of research has established that the production of voice is largely a mechanical process: i.e., the sustained vibration of the vocal folds driven by the glottal air flow. Since one only has a single pair of vocal folds, the versatility comes with the ability to change the mechanical status of the vocal folds, including vocal fold length and thickness, tension, and level of adduction, through activation of the laryngeal muscles. However, the relationship between laryngeal muscle activity and the characteristics of voice is not well understood due to limitations in experimental observation and simplifications in modelling and simulations. The science is still far behind the art. The current research aims to investigate first the relationship between laryngeal muscle activation and the posture of the vocal folds and second the relationship between voice source characteristics and vocal fold mechanical status using more comprehensive numerical models and simulations, thus improving the understanding of the roles of each laryngeal muscle in voice control. To do so, (1) the mechanics involved in vocal fold posturing and vibration, especially muscle contraction; (2) the realistic anatomical structure of the larynx must be considered properly. To achieve this goal, a numerical model of the larynx as realistic as possible was built. The geometry of the laryngeal components was reconstructed from high resolution MRI (Magnetic Resonance Imaging) data of an excised canine larynx, which makes more accurate the representation of the muscles and their sub-compartments, cartilages, and other important anatomical features of the larynx. A previously proposed muscle activation model was implemented in a 3D finite element package and applied to the larynx model to simulate the action of laryngeal muscles. After validation of the numerical model against experimental data, extensive parametric studies involving different combination of muscle activations were conducted to investigate how the voice source is controlled with laryngeal muscles. In the course of this study, some work was done to couple the same finite element tool with a Genetic Algorithm program to inversely determine model parameters in biomechanical models. The method was applied in a collaborated study on shape changes of a fish fin during swimming. This study is presented as a separate chapter at the end of this thesis. The method has potential application in determining parameters in vocal fold models and optimizing clinical vocal fold procedures. This thesis is essentially an assembly of the papers published by the author during the doctoral study, with the addition of an introductory chapter. Chapter 1 reviews the overall principles of voice production, the biomechanical basis of voice control, and past studies on voice control with a focus on the fundamental frequency. Chapter 2 describes the major numerical methods employed in this research with an emphasis on the finite element method. The muscle activation model is also described in this chapter. Chapter 3 describes the building of the larynx model from MRI data and its partial validation. Chapter 4 presents the application of the larynx model to posturing studies, including parametric activation of muscle groups and specific topics related to vocal fold posturing. Chapter 5 describes the change of vocal fold vibration dynamics under the influence of the interaction of the cricothyroid muscle and the thyroarytenoid muscle. The Flow-structure interaction simulations was realized by coupling the larynx model to a simple Bernoulli flow model and a two-stage simulation technique. Chapter 6 concludes the current thesis study. Suggestions for future studies are proposed. Chapter 7 is an independent study that is not related to voice control. It describes a numerical framework that inversely determines and validates model parameters of biomechanical models. The application of the proposed framework to a finite element model of a fish fin is presented