The care and rehabilitation of individuals after lower limb amputation presents a substantial and growing socioeconomic challenge. Clinical outcome is closely linked to successful functional rehabilitation with a prosthetic limb, which depends upon comfortable prosthetic limb - residual limb load transfer. Despite early interest in the 1980s, the amputated limb has received considerably less attention in computational biomechanical analysis than other subjects, such as arthroplasty. This systematic literature review investigates the state of the art in residual limb finite element analysis published since 2000. The identified studies were grouped into the following categories: (1) residuum-prosthesis interface mechanics; (2) residuum soft tissue internal mechanics; (3) identification of residuum tissue characteristics; (4) proposals for incorporating FEA into the prosthesis fitting process; (5) analysis of the influence of prosthetic componentry concepts to improve load transfer to the residuum, such as the monolimb and structural socket compliance; and (6) analysis of osseointegrated (OI) prostheses. The state of the art is critically appraised in order to form recommendations for future modeling studies in terms of geometry, material properties, boundary conditions, interface models, and relevant but un-investigated issues. Finally, the practical implementation of these approaches is discussed.

Background: Understanding how prostheses are used in everyday life is central to the design, provision and evaluation of prosthetic devices and associated services. This paper reviews the scientific literature on methodologies and technologies that have been used to assess the daily use of both upper- and lower-limb prostheses. It discusses the types of studies that have been undertaken, the technologies used to monitor physical activity, the benefits of monitoring daily living and the barriers to long-term monitoring, with particular focus on low-resource settings.Methods: A systematic literature search was conducted in PubMed, Web of Science, Scopus, CINAHL and EMBASE of studies that monitored the activity of prosthesis users during daily-living.Results: Sixty lower-limb studies and 9 upper-limb studies were identified for inclusion in the review. The first studies in the lower-limb field date from the 1990s and the number has increased steadily since the early 2000s. In contrast, the studies in the upper-limb field have only begun to emerge over the past few years. The early lower-limb studies focused on the development or validation of actimeters, algorithms and/or scores for activity classification. However, most of the recent lower-limb studies used activity monitoring to compare prosthetic components. The lower-limb studies mainly used step-counts as their only measure of activity, focusing on the amount of activity, not the type and quality of movements. In comparison, the small number of upper-limb studies were fairly evenly spread between development of algorithms, comparison of everyday activity to clinical scores, and comparison of different prosthesis user populations. Most upper-limb papers reported the degree of symmetry in activity levels between the arm with the prosthesis and the intact arm.Conclusions: Activity monitoring technology used in conjunction with clinical scores and user feedback, offers significant insights into how prostheses are used and whether they meet the user’s requirements. However, the cost, limited battery-life and lack of availability in many countries mean that using sensors to understand the daily use of prostheses and the types of activity being performed has not yet become a feasible standard clinical practice. This review provides recommendations for the research and clinical communities to advance this area for the benefit of prosthesis users.

Computational biomechanical models are useful tools for supporting orthopedic implant design and surgical decision making, but because they are a simplification of the clinical scenario they must be carefully validated to ensure that they are still representative. The goal of this study was to assess the validity of the generation process of a structural finite element model of the proximal femur employing the digital image correlation (DIC) strain measurement technique. A finite element analysis model of the proximal femur subjected to gait loading was generated from a CT scan of an analog composite femur, and its predicted mechanical behavior was compared with an experimental model. Whereas previous studies have employed strain gauging to obtain discreet point data for validation, in this study DIC was used for full field quantified comparison of the predicted and experimentally measured strains. The strain predicted by the computational model was in good agreement with experimental measurements, with $R2$ correlation values from 0.83 to 0.92 between the simulation and the tests. The sensitivity and repeatability of the strain measurements were comparable to or better than values reported in the literature for other DIC tests on tissue specimens. The experimental-model correlation was in the same range as values obtained from strain gauging, but the DIC technique produced more detailed, full field data and is potentially easier to use. As such, the findings supported the validity of the model generation process, giving greater confidence in the model’s predictions, and digital image correlation was demonstrated as a useful tool for the validation of biomechanical models.

It has been proposed that finite element analysis can complement clinical decision making for the appropriate design and manufacture of prosthetic sockets for amputees. However, clinical translation has not been achieved, in part due to lengthy solver times and the complexity involved in model development. In this study, a parametric model was created, informed by variation in (i) population-driven residuum shape morphology, (ii) soft tissue compliance and (iii) prosthetic socket design. A Kriging surrogate model was fitted to the response of the analyses across the design space enabling prediction for new residual limb morphologies and socket designs. It was predicted that morphological variability and prosthetic socket design had a substantial effect on socket-limb interfacial pressure and shear conditions as well as sub-dermal soft tissue strains. These relationships were investigated with a higher resolution of anatomical, surgical and design variability than previously reported, with a reduction in computational expense of six orders of magnitude. This enabled real-time predictions (1.6 ms) with error vs the analytical solutions of < 4 kPa in pressure at residuum tip, and < 3% in soft tissue strain. As such, this framework represents a substantial step towards implementation of finite element analysis in the prosthetics clinic.

A detailed understanding of the changes in load transfer due to implantation is necessary to identify potential failure mechanisms of orthopedic implants. Computational finite element (FE) models provide full field data on intact and implanted bone structures, but their validity must be assessed for clinical relevance. The aim of this study was to test the validity of FE predicted strain distributions for the intact and implanted pelvis using the digital image correlation (DIC) strain measurement technique. FE models of an in vitro hemipelvis test setup were produced, both intact and implanted with an acetabular cup. Strain predictions were compared to DIC and strain rosette measurements. Regression analysis indicated a strong linear relationship between the measured and predicted strains, with a high correlation coefficient (R = 0.956 intact, 0.938 implanted) and a low standard error of the estimate (SE = 69.53 με, 75.09 με). Moreover, close agreement between the strain rosette and DIC measurements improved confidence in the validity of the DIC technique. The FE model therefore was supported as a valid predictor of the measured strain distribution in the intact and implanted composite pelvis models, confirming its suitability for further computational investigations.