475 research outputs found

    Quantification of knee extensor muscle forces: a multimodality approach

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    Given the growing interest of using musculoskeletal (MSK) models in a large number of clinical applications for quantifying the internal loading of the human MSK system, verification and validation of the model’s predictions, especially at the knee joint, have remained as one of the biggest challenges in the use of the models as clinical tools. This thesis proposes a methodology for more accurate quantification of knee extensor forces by exploring different experimental and modelling techniques that can be used to enhance the process of verification and validation of the knee joint model within the MSK models for transforming the models to a viable clinical tool. In this methodology, an experimental protocol was developed for simultaneous measurement of the knee joint motion, torques, external forces and muscular activation during an isolated knee extension exercise. This experimental protocol was tested on a cohort of 11 male subjects and the measurements were used to quantify knee extensor forces using two different MSK models representing a simplified model of the knee extensor mechanism and a previously-developed three-dimensional MSK model of the lower limb. The quantified knee extensor forces from the MSK models were then compared to evaluate the performance of the models for quantifying knee extensor forces. The MSK models were also used to investigate the sensitivity of the calculated knee extensor forces to key modelling parameters of the knee including the method of quantifying the knee centre of rotation and the effect of joint translation during motion. In addition, the feasibility of an emerging ultrasound-based imaging technique (shear wave elastography) for direct quantification of the physiologically-relevant musculotendon forces was investigated. The results in this thesis showed that a simplified model of the knee can be reliably used during a controlled planar activity as a computationally-fast and effective tool for hierarchical verification of the knee joint model in optimisation-based large-scale MSK models to provide more confidence in the outputs of the models. Furthermore, the calculation of knee extensor muscle forces has been found to be sensitive to knee joint translation (moving centre of rotation of the knee), highlighting the importance of this modelling parameter for quantifying physiologically-realistic knee muscle forces in the MSK models. It was also demonstrated how the movement of the knee axis of rotation during motion can be used as an intuitive tool for understanding the functional anatomy of the knee joint. Moreover, the findings in this thesis indicated that the shear wave elastography technique can be potentially used as a novel method for direct quantification of the physiologically-relevant musculotendon forces for independent validation of the predictions of musculotendon forces from the MSK models.Open Acces

    Specimen-Specific Natural, Pathological, and Implanted Knee Mechanics Using Finite Element Modeling

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    There is an increasing incidence of knee pain and injury among the population, and increasing demand for higher knee function in total knee replacement designs. As a result, clinicians and implant manufacturers are interested in improving patient outcomes, and evaluation of knee mechanics is essential for better diagnosis and repair of knee pathologies. Common knee pathologies include osteoarthritis (degradation of the articulating surfaces), patellofemoral pain, and cruciate ligament injury and/or rupture. The complex behavior of knee motion presents unique challenges in the diagnosis of knee pathology and restoration of healthy knee function. Quantifying knee mechanics is essential for developing successful rehabilitation therapies and surgical treatments. Researchers have used in-vitro and in-vivo experiments to quantify joint kinematics and loading, but experiments can be costly and time-intensive, and contact and ligament mechanics can be difficult to measure directly. Computational modeling can complement experimental studies by providing cost-effective solutions for quantifying joint and soft tissue forces. Musculoskeletal models have been used to measure whole-body motion, and predict joint and muscle forces, but these models can lack detail and accuracy at the joint-level. Finite element modeling provides accurate solutions of the internal stress/strain behavior of bone and soft tissue using subject-specific geometry and complex contact and material representations. While previous FE modeling has been used to simulate injury and repair, models are commonly based on literature description or average knee behavior. The research presented in this dissertation focused on developing subject-specific representations of the TF and PF joints including calibration and validation to experimental data for healthy, pathological, and implanted knee conditions. A combination of in-vitro experiment and modeling was used to compare healthy and cruciate-deficient joint mechanics, and develop subject-specific computational representations. Insight from in-vitro testing supported in-vivo simulations of healthy and implanted subjects, in which PF mechanics were compared between two common patellar component designs and the impact of cruciate ligament variability on joint kinematics and loads was assessed. The suite of computational models developed in this dissertation can be used to investigate knee pathologies to better inform clinicians on the mechanisms surrounding injury, support the diagnosis of at-risk patients, explore rehabilitation and surgical techniques for repair, and support decision-making for new innovative implant designs

    SAR: Generalization of Physiological Agility and Dexterity via Synergistic Action Representation

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    Learning effective continuous control policies in high-dimensional systems, including musculoskeletal agents, remains a significant challenge. Over the course of biological evolution, organisms have developed robust mechanisms for overcoming this complexity to learn highly sophisticated strategies for motor control. What accounts for this robust behavioral flexibility? Modular control via muscle synergies, i.e. coordinated muscle co-contractions, is considered to be one putative mechanism that enables organisms to learn muscle control in a simplified and generalizable action space. Drawing inspiration from this evolved motor control strategy, we use physiologically accurate human hand and leg models as a testbed for determining the extent to which a Synergistic Action Representation (SAR) acquired from simpler tasks facilitates learning more complex tasks. We find in both cases that SAR-exploiting policies significantly outperform end-to-end reinforcement learning. Policies trained with SAR were able to achieve robust locomotion on a wide set of terrains with high sample efficiency, while baseline approaches failed to learn meaningful behaviors. Additionally, policies trained with SAR on a multiobject manipulation task significantly outperformed (>70% success) baseline approaches (<20% success). Both of these SAR-exploiting policies were also found to generalize zero-shot to out-of-domain environmental conditions, while policies that did not adopt SAR failed to generalize. Finally, we establish the generality of SAR on broader high-dimensional control problems using a robotic manipulation task set and a full-body humanoid locomotion task. To the best of our knowledge, this investigation is the first of its kind to present an end-to-end pipeline for discovering synergies and using this representation to learn high-dimensional continuous control across a wide diversity of tasks.Comment: Accepted to RSS 202

    Musculoskeletal modeling and finite element analysis of the proximal juvenile femur

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    The influence of mechanical loading on bone modelling and remodelling has been, and still is the subject of many studies. It is widely accepted that the internal structure of long bones is orientated to the strains experienced throughout activities, and the morphometry of the bones are as a result of the loading. Although other influences play a role in bone development including, hormonal, nutritional and genetic. The internal structure is orientated in such a way that it transfers the loads experienced without being excessive in weight, providing an efficient weight bearing structure. Many researchers have analysed the adult femur but little work has been undertaken to understand femoral development in juveniles. Therefore the aim this work was to develop an understanding of the mechanical stresses and strains that the femur experiences during growth.The juvenile femur changes dramatically throughout growth. These changes occur from prenatal through to full maturity. The most notable include the ossification from a highly cartilaginous structure in the early years of development, to bone at ~18 years old, an increase in the length and angle of the neck, a change in the shaft torsion and a change in the bicondylar angle. Similarly, the development of movement patterns and locomotion in humans changes significantly throughout growth. Movement is restricted in utero, in neonates the movement begins to engage muscular activity, at 6 months a baby is usually able to sit upright; 9 months crawling begins; by 1 year old there is the ability to walk without support and at 4 years old an adult like gait pattern has developed. Full adult gait pattern has been documented to be achieved between 8-11 years old.In this work through gait analysis and musculoskeletal modelling the loads which the femur experiences at specific stages/ages of bipedal locomotion are analysed. Finite element analyses were then performed to develop an understanding of the stresses and strains of the proximal juvenile femur in relation to the attainment and development of bipedal gait. This was achieved by evaluating changes in these mechanical stresses and strains throughout different ages, relating them to the variations discovered in the gait patterns.Digitisation of the femora was performed on four specimens; prenatal, 3 years old, 7 years old and an adult. Following the scanning of the specimens in a micro CT scanner, some restoration to the damaged samples was required. Furthermore the dry samples were incomplete, and the models were needed to be modelled to accurately resemble fully intact femurs. The CT scans contained the full shaft however were missing the fully articulated proximal femur, due to the dry nature of the specimens the cartilages were absent. MRI scans which contained the femoral head data but were missing the full shaft were merged with the CT data to create a fully articulated femur for use in subsequent modelling.Gait analysis was performed on five children aged from 3-7 years old, with an average of five adults gait data used for comparison. The analysis showed that kinematic data was similar between all ages, however kinetic results revealed some differences. Ground reaction force in the 3 year old showed a higher heel strike compared to a higher toe off observed in adult during the gait cycle, indicating a lack of control in the 3 year old. Furthermore the 3 year old, compared to the other ages, had different values in joint moments. These joint moment results in particular played a role in the muscle forces produced from the musculoskeletal modelling.To obtain the muscle force data required for the FEA, musculoskeletal models were built. Testing the reliability of the musculoskeletal model was performed comparing the kinematic and kinetic data from the musculoskeletal modelling against the data obtained from the motion capture system. A good agreement was found between these data sets with the kinematics having the largest difference in the ankle plantar flexion of 8.6°. The kinetic results revealed almost exact matches. Further testing was attempted between the muscle force data and collected EMG. The collected EMG matched reported EMG in the literature and the onset and offset times of muscle activity corresponded well to muscle force peaks produced in the musculoskeletal model. Comparisons between the EMG and force through calculating the EMG as a force were inconclusive, although a degree of accuracy was shown but a more comprehensive method is required. It was concluded that with the accuracy of the kinematic and kinetic results the musculoskeletal modelling was accurate enough to give a true representation of physiological muscle forces to be modelled during FEA.Analysis of the musculoskeletal modelling results in the children revealed that the 3 year old had the highest significance between all the age groups. With the greatest significance in the hip flexors and abductors throughout the gait cycle. Joint reaction forces as a percentage of bodyweight were found to be much higher in the juvenile models. The adult model had a value of 265% bodyweight whereas the 3 year old showed a reaction force of 537% bodyweight. These differences observed in the musculoskeletal modelling had a direct effect on the FEA because the loads calculated here were applied to the finite element models to evaluate the effects that these would have on the stresses and strains during growth and development of the femur.FE models were built to represent a 3 year old, 7 year old and adult femur. Age specific loads calculated over 100% of a gait cycle, were applied to the models. The stress/strain analysis revealed some differences between the models but in general the areas exposed to high and low strain levels were similar. The similarities could suggest that each model was structurally adapted to the loads the femur regularly experiences. The thesis was successful in evaluating the stress and strain distribution apparent in the developing femur. However the work would be advanced by evaluating models from age ranges with a much more varied movement pattern i.e. crawling. This would increase an understanding of the structural optimisation of the femur

    Tele-impedance based assistive control for a compliant knee exoskeleton

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    This paper presents a tele-impedance based assistive control scheme for a knee exoskeleton device. The proposed controller captures the user’s intent to generate task-related assistive torques by means of the exoskeleton in different phases of the subject’s normal activity. To do so, a detailed musculoskeletal model of the human knee is developed and experimentally calibrated to best match the user’s kinematic and dynamic behavior. Three dominant antagonistic muscle pairs are used in our model, in which electromyography (EMG) signals are acquired, processed and used for the estimation of the knee joint torque, trajectory and the stiffness trend, in real time. The estimated stiffness trend is then scaled and mapped to a task-related stiffness interval to agree with the desired degree of assistance. The desired stiffness and equilibrium trajectories are then tracked by the exoskeleton’s impedance controller. As a consequence, while minimum muscular activity corresponds to low stiffness, i.e. highly transparent motion, higher co-contractions result in a stiffer joint and a greater level of assistance. To evaluate the robustness of the proposed technique, a study of the dynamics of the human–exoskeleton system is conducted, while the stability in the steady state and transient condition is investigated. In addition, experimental results of standing-up and sitting-down tasks are demonstrated to further investigate the capabilities of the controller. The results indicate that the compliant knee exoskeleton, incorporating the proposed tele-impedance controller, can effectively generate assistive actions that are volitionally and intuitively controlled by the user’s muscle activity
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