Nonlinear Elastic Material Property Estimation of Lower Extremity Residual Limb Tissues

The interface stresses between the residual limb and prosthetic socket have been studied to investigate prosthetic fit. Finite-element models of the residual limb-prosthetic socket interface facilitate investigation of the mechanical interface and may serve as a potential tool for future prosthetic socket design. However, the success of such residual limb models to date has been limited, in large part due to inadequate material formulations used to approximate the mechanical behavior of residual limb soft tissues. Nonlinear finite-element analysis was used to simulate force-displacement data obtained during in vivo rate-controlled (1, 5, and 10 mm/s) cyclic indentation of the residual limb soft tissues of seven individuals with transtibial amputation. The finite-element models facilitated determination of an appropriate set of nonlinear elastic material coefficients for bulk soft tissue at discrete clinically relevant test locations. Axisymmetric finite-element models of the residual limb bulk soft tissue in the vicinity of the test location, the socket wall and the indentor tip were developed incorporating contact analysis, large displacement, and large strain, and the James-Green-Simpson nonlinear elastic material formulation. Model dimensions were based on medical imaging studies of the residual limbs. The material coefficients were selected such that the normalized sum of square error (NSSE) between the experimental and finite-element model indentor tip reaction force was minimized. A total of 95% of the experimental data were simulated using the James-Green-Simpson material formulation with an NSSE less than 5%. The respective James-Green-Simpson material coefficients varied with subject, test location, and indentation rate. Therefore, these coefficients cannot be readily extrapolated to other sites or individuals, or to the same site and individual some time after testing

Mobility in individuals with traumatic lower-limb injuries : implications for device design, surgical intervention and rehabilitation therapies

Traumatic injuries to the extremities are commonly observed in emergency room patients and military personnel in combat. Restoring high mobility and functionality is a primary goal post-injury, which may require the use of rehabilitative devices, surgical interventions, and rehabilitation therapies. The research detailed in this dissertation investigates specific elements of these approaches through the use of experimental study and modeling and simulation. In the first study, the influence of passive-dynamic ankle-foot orthosis bending axis on the gait performance of limb salvage subjects was investigated. Bending axis location was altered by fabricating customized orthosis components using additive manufacturing and was tested in a gait laboratory. Altering bending axis location did not result in large or consistent changes in gait measures, however subjects expressed strong preferences for bending axis condition and preference was strongly related to specific gait measures. This suggests that preference and comfort are important factors guiding the prescription of bending axis location. In the second study, musculoskeletal modeling was used to examine the influence of transfemoral amputation surgical techniques on muscle capacity to generate forces and moments about the hip. Muscle reattachment tension and stabilization were shown to be critical parameters for post-amputation capacity, which supports the use of myodesis stabilization (muscle is reattached directly to bone) in amputation procedures. In the third study, a forward dynamics simulation of transfemoral amputee gait was developed and used to examine individual muscle and prosthesis contributions to walking subtasks. The residual hip muscles, and intact ankle, knee, and hip muscles worked synergistically to provide body support, anteroposterior propulsion, mediolateral control, and leg swing. Increased contributions of contralateral muscles to ipsilateral subtasks as well as increased duration of specific muscle contributions were observed in comparison to non-amputee and transtibial amputee walking. These findings can be used to help develop targeted rehabilitation therapies and improve transfemoral amputee locomotion. Through elucidating the influence of PD-AFO bending axis on gait performance as well as the influence of transfemoral amputation surgical techniques on muscle capacity and function, this research provides a foundation for improved rehabilitation outcomes, and thus mobility for individuals who have experienced traumatic lower-limb injuries.Mechanical Engineerin

Deep Reinforcement Learning for Physics-Based Musculoskeletal Simulations of Healthy Subjects and Transfemoral Prostheses’ Users During Normal Walking

This paper proposes to use deep reinforcement learning for the simulation of physics-based musculoskeletal models of both healthy subjects and transfemoral prostheses’ users during normal level-ground walking. The deep reinforcement learning algorithm is based on the proximal policy optimization approach in combination with imitation learning to guarantee a natural walking gait while reducing the computational time of the training. Firstly, the optimization algorithm is implemented for the OpenSim model of a healthy subject and validated with experimental data from a public data-set. Afterwards, the optimization algorithm is implemented for the OpenSim model of a generic transfemoral prosthesis’ user, which has been obtained by reducing the number of muscles around the knee and ankle joints and, specifically, by keeping only the uniarticular ones. The model of the transfemoral prosthesis’ user shows a stable gait, with a forward dynamic comparable to the healthy subject’s, yet using higher muscles’ forces. Even though the computed muscles’ forces could not be directly used as control inputs for muscle-like linear actuators due to their pattern, this study paves the way for using deep reinforcement learning for the design of the control architecture of transfemoral prostheses

Powered Transtibial Prosthetic Device Control System Design, Implementation and Testing

A powered lower limb prosthesis, which consists of a four bar mechanism, a torsional spring and a brushed DC motor, was previously designed and fabricated. To regulate the motor power input, a two level controller was proposed and built. The control algorithm includes a higher level finite state controller and lower level PID controllers. To implement the control system, a digital signal processor (DSP) control board and MATLAB Simulink were used to realize the higher level control and a DC motor controller was used to realize the lower level PID control. Sensors were selected to provide the required feedback. The entire control system was implemented on a convenient to carry backpack. Amputee subject testing was performed to obtain some experimental verification of the design. The results showed that the control system performed consistently with the designed control algorithm and did assist in the amputee’s walking. Compared to a currently available powered prosthesis, this control is simple in structure and able to mimic the nonlinear behavior of the ankle closely

A Generalized Method for Predictive Simulation-Based Lower Limb Prosthesis Design

Lower limb prostheses are designed to replace the functions and form of the missing biological anatomy. These functions are hypothesized to improve user outcome measures which are negatively affected by receiving an amputation – such as metabolic cost of transport, preferred walking speed, and perceived discomfort during walking. However, the effect of these design functions on the targeted outcome measures is highly variable, suggesting that these relationships are not fully understood. Biomechanics simulation and modeling tools are increasingly capable of analyzing the effects of a design on the resulting user gait. In this work, prothesis-aided gait is optimized in simulation to reduce both muscle effort and peak loads on the residual limb using a generalized prosthesis model. Compared to a traditional revolute powered ankle joint model, a two degree-of freedom generalized model reduced muscle activations by 50% and peak loads by 15%. Simulated prosthesis behaviors corresponding to the optimal gait patterns were translated into a two degree-of-freedom ankle-foot prosthesis design with powered bidirectional linear translation and plantarflexion. The prototype is capable of delivering up to 171 N-m of plantarflexion torque and 499 N of translation force, with 15° dorsi-/35° plantarflexion and 10 cm translation range of motion. The mass and height of the ankle-foot are 2.29 kg and 19.5 cm, respectively. The mass of the entire system including the wearable offboard system is 8.58 kg. This platform is designed to emulate the behavior of the simulated prosthesis, as well as be configurable to emulate alternate behaviors obtained from simulations with different optimization objectives. The prototype is controlled to replicate simulated walking patterns using a high level finite state controller, mid-level stiffness controller, and low level load controller. Closed loop load control has bandwidth of 15 Hz in translation and 7.2 Hz in flexion. Load tracking during walking with a single able-bodied human subject ranges from 93 to 159 N in translation and 4.6 to 21.3 N-m in flexion. The contribution of this work is to provide a framework for predictive simulation-based prosthesis design, evidence of its practical implementation, and the experimental tools to validate future predictive simulation studies

PREDICTIVE SIMULATION OF HUMAN MOVEMENT AND APPLICATIONS TO ASSISTIVE DEVICE DESIGN AND CONTROL

Predictive simulation based on dynamic optimization using musculoskeletal models is a powerful approach for studying biomechanics of human gait. Predictive simulation can be used for a variety of applications from designing assistive devices to testing theories of motor controls. However, one of the challenges in formulating the predictive dynamic optimization problem is that the cost function, which represents the underlying goal of the walking task (e.g., minimal energy consumption) is generally unknown and is assumed a priori. While different studies used different cost functions, the qualities of the gaits with those cost functions were often not provided. Therefore, this dissertation evaluates and examines different cost function forms for dynamic simulation of human walking. The problem of the walking cost function determination was cast as a bilevel optimization, which was solved using a nested evolutionary approach. The results showed cost functions based on a weighted combination of muscle-based performance criteria (e.g., metabolic cost, muscle fatigue), gait smoothness, and gait stability led to better walking solutions compared to any cost functions only based on muscle performance criteria. Further evaluations of the walking cost functions were done in the simulation cases of human walking augmented with assistive devices such as prosthesis and exoskeleton. The simulations of augmented walking were comparable to the experimental results, which suggests the potential of using the simulation approach to address problems of finding assistive device design and control