Biomechanics of transfemoral amputees fitted with osseointegrated fixation: Loading data for evidence-based practice

This presentation will provide an overview of the load applied on the residuum of transfemoral amputees fitted with an osseointegrated fixation during (A) rehabilitation, including static and dynamic load bearing exercises (e.g., rowing, adduction, abduction, squat, cycling, walking with aids), and (B) activities of daily living including standardized activities (e.g., level walking in straight line and around a circle, ascending and descending slopes and stairs) and activities in real world environments. A particular emphasis will be placed on the outcomes of several studies for an evidence-based design of the rehabilitation program and components of the fixation (e.g., implant, abutment). It is anticipated that this work might contribute to the current effort aiming at shortening the rehabilitation program and reducing the incidence of replacement of abutments

The effect of cortical thickness and thread profile dimensions on stress and strain in bone-anchored implants for amputation prostheses

Skeletal attachment of limb prostheses ensures load transfer between the prosthetic leg and the skeleton. For individuals with lower limb amputation, these loads may be of substantial magnitude. To optimize the design of such systems, knowledge about the structural interplay between implant design features, dimensional changes, and material properties of the implant and the surrounding bone is needed. Here, we present the results from a parametric finite element investigation on a generic bone-anchored implant system of screw design, exposed to external loads corresponding to average and high ambulatory loading. Of the investigated parameters, cortical thickness had the largest effect on the stress and strain in the bone-anchored implant and in the cortical bone. 36%–44% reductions in maximum longitudinal stress in the bone-anchored implant was observed as a result of increased cortical thickness from 2 mm to 5 mm. A change in thread depth from 1.5 mm to 0.75 mm resulted in 20%–22% and 10%–18% reductions in maximum longitudinal stress in the bone-anchored implant at 2 mm and 5 mm cortical thickness respectively. The effect of changes in the thread root radius was less prominent, with 8% reduction in the maximum longitudinal stress in the bone-anchored implant being the largest observed effect, resulting from an increased thread root radius from 0.1 mm to 0.5 mm at a thread depth of 1.5 mm. Autologous transplantation of bone tissue distal to the fixture resulted in reductions in the longitudinal stress in the percutaneous abutment. The observed stress reduction of 10%–31% was dependent on the stiffness of the transplanted bone graft and the cortical thickness of surrounding bone. Results from this investigation may guide structural design optimization for bone-anchored implant systems for attachment of limb prostheses

Load on osseointegrated fixation of a transfemoral amputee during a fall: determination of the time and duration of descent

Mitigation of fall-related injuries for populations of transfemoral amputees fitted with a socket or an osseointegrated fixation is challenging. Wearing a protective device fitted within the prosthesis might be a possible solution, provided that issues with automated fall detection and time of deployment of the protective mechanism are solved. The first objective of this study was to give some examples of the times and durations of descent during a real forward fall of a transfemoral amputee that occurred inadvertently while attending a gait measurement session to assess the load applied on the residuum. The second objective was to present five semi-automated methods of detection of the time of descent using the load data. The load was measured directly at 200 Hz using a six-channel transducer. The average time and duration of descent were 242±42 ms [145 ms-310 ms] and 619±42 ms [550 ms -715 ms], respectively. This study demonstrated that the transition between walking and falling was characterised by times of descent that occurred sequentially. The sensitivity and specificity of an automated algorithm might be improved by combining several methods of detection based on the deviation of the loads measured from their own trends and from a template previously established

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

On the Utility of Representation Learning Algorithms for Myoelectric Interfacing

Electrical activity produced by muscles during voluntary movement is a reflection of the firing patterns of relevant motor neurons and, by extension, the latent motor intent driving the movement. Once transduced via electromyography (EMG) and converted into digital form, this activity can be processed to provide an estimate of the original motor intent and is as such a feasible basis for non-invasive efferent neural interfacing. EMG-based motor intent decoding has so far received the most attention in the field of upper-limb prosthetics, where alternative means of interfacing are scarce and the utility of better control apparent. Whereas myoelectric prostheses have been available since the 1960s, available EMG control interfaces still lag behind the mechanical capabilities of the artificial limbs they are intended to steer—a gap at least partially due to limitations in current methods for translating EMG into appropriate motion commands. As the relationship between EMG signals and concurrent effector kinematics is highly non-linear and apparently stochastic, finding ways to accurately extract and combine relevant information from across electrode sites is still an active area of inquiry.This dissertation comprises an introduction and eight papers that explore issues afflicting the status quo of myoelectric decoding and possible solutions, all related through their use of learning algorithms and deep Artificial Neural Network (ANN) models. Paper I presents a Convolutional Neural Network (CNN) for multi-label movement decoding of high-density surface EMG (HD-sEMG) signals. Inspired by the successful use of CNNs in Paper I and the work of others, Paper II presents a method for automatic design of CNN architectures for use in myocontrol. Paper III introduces an ANN architecture with an appertaining training framework from which simultaneous and proportional control emerges. Paper Iv introduce a dataset of HD-sEMG signals for use with learning algorithms. Paper v applies a Recurrent Neural Network (RNN) model to decode finger forces from intramuscular EMG. Paper vI introduces a Transformer model for myoelectric interfacing that do not need additional training data to function with previously unseen users. Paper vII compares the performance of a Long Short-Term Memory (LSTM) network to that of classical pattern recognition algorithms. Lastly, paper vIII describes a framework for synthesizing EMG from multi-articulate gestures intended to reduce training burden

Performance evaluation of an ensemble neural network system of estimating transtibial prosthetic socket pressures during standing, walking and condition perturbation.

Providing suitable prosthetic sockets for the restoration of function following lower-limb amputation remains a significant issue in medical device prescription. Poorly designed sockets are associated with discomfort, poor quality function and injury, with quality linked to the capability of the socket to adequately distribute the forces from ambulation. Despite this link, systems of measuring stump-socket interface pressure have not seen use in clinical practice, in part due to limitations in functional performance. A technique using neural networks to relate external socket deformation to the internal pressure distribution was recently developed: this method has several advantages over contemporary systems but had not been evaluated in detail in dynamic situations. A wireless system estimating transtibial socket pressure distribution was produced. When supplied with simulated socket loads, an estimate produced from a group of networks (an ensemble) demonstrated improved accuracy and reduced variance. Work was undertaken to identify optimal design in terms of input data conditioning and post-estimate correction. This demonstrated that these can provide significant accuracy and reliability improvements. Measurements were taken from two transtibial amputees during standing, walking, walking on slopes, walking with coronal plane misalignment and walking with an alternative socket liner. An evaluation of the contributions to variance confirmed the applicability of ensembles in this application. The system proved capable recording significant differences in socket load distribution between different prosthesis configurations. For future investigation, this demonstrates that the technique is sensitive enough to examine the changes in the application of force which are present during daily use, device set-up and common fault conditions. The results of this study support further development of the practical aspects of the system, future work in producing a realistic load training system and extrapolation of results to other sockets, structures and engineering problems

Osseointegrated Oral implants

In the past, osseointegration was regarded to be a mode of implant anchorage that simulated a simple wound healing phenomenon. Today, we have evidence that osseointegration is, in fact, a foreign body reaction that involves an immunologically derived bony demarcation of an implant to shield it off from the tissues. Marginal bone resorption around an oral implant cannot be properly understood without realizing the foreign body nature of the implant itself. Whereas the immunological response as such is positive for implant longevity, adverse immunological reactions may cause marginal bone loss in combination with combined factors. Combined factors include the hardware, clinical handling as well as patient characteristics that, even if each one of these factors only produce subliminal trauma, when acting together they may result in loss of marginal bone. The role of bacteria in the process of marginal bone loss is smaller than previously believed due to combined defense mechanisms of inflammation and immunological reactions, but if the defense is failing we may see bacterially induced marginal bone loss as well. However, problems with loss of marginal bone threatening implant survival remains relatively uncommon; we have today 10 years of clinical documentation of five different types of implant displaying a failure rate in the range of only 1 to 4 %

Finite Element Modeling to Aid in Refining the Rehabilitation of Amputees Using Osseointegrated Prostheses

The direct anchorage of a lower-limb prosthesis to the bone has been shown to be an excellent alternative for amputees experiencing complications in using a conventional prosthetic socket. After surgical implantation, amputees have to go through a weight bearing exercise program to prepare the bone to tolerate forces and promote bone-remodeling. Currently, the load magnitude prescribed by the clinician is measured by a weight scale which reports only the axial force in the limb. Previous study using a load transducer revealed that in addition to the axial force there were other forces and moments. This study develops a FE model and utilizes our load data to investigate the stress distribution at the bone-implant interface. The model shows that the stress distribution could be highly non-uniform during the exercise. Bone-implant interface stress has certain implications in pain adaptation and bone-remodeling, and a good understanding of it can assist in future attempts to refine and shorten the period of rehabilitation exercise

Advances in Micro and Nano Manufacturing: Process Modeling and Applications

Micro- and nanomanufacturing technologies have been researched and developed in the industrial environment with the goal of supporting product miniaturization and the integration of new functionalities. The technological development of new materials and processing methods needs to be supported by predictive models which can simulate the interactions between materials, process states, and product properties. In comparison with the conventional manufacturing scale, micro- and nanoscale technologies require the study of different mechanical, thermal, and fluid dynamics, phenomena which need to be assessed and modeled.This Special Issue is dedicated to advances in the modeling of micro- and nanomanufacturing processes. The development of new models, validation of state-of-the-art modeling strategies, and approaches to material model calibration are presented. The goal is to provide state-of-the-art examples of the use of modeling and simulation in micro- and nanomanufacturing processes, promoting the diffusion and development of these technologies