Generation of subject-specific, dynamic, multisegment ankle and foot models to improve orthotic design: a feasibility study

Abstract

BackgroundCurrently, custom foot and ankle orthosis prescription and design tend to be based on traditional techniques, which can result in devices which vary greatly between clinicians and repeat prescription. The use of computational models of the foot may give further insight in the biomechanical effects of these devices and allow a more standardised approach to be taken to their design, however due to the complexity of the foot the models must be highly detailed and dynamic.Methods/DesignFunctional and anatomical datasets will be collected in a multicentre study from 10 healthy participants and 15 patients requiring orthotic devices. The patient group will include individuals with metarsalgia, flexible flat foot and drop foot.Each participant will undergo a clinical foot function assessment, 3D surface scans of the foot under different loading conditions, and detailed gait analysis including kinematic, kinetic, muscle activity and plantar pressure measurements in both barefoot and shod conditions. Following this each participant will undergo computed tomography (CT) imaging of their foot and ankle under a range of loads and positions while plantar pressures are recorded. A further subgroup of participants will undergo magnetic resonance imaging (MRI) of the foot and ankle.Imaging data will be segmented to derive the geometry of the bones and the orientation of the joint axes. Insertion points of muscles and ligaments will be determined from the MRI and CT-scans and soft tissue material properties computed from the loaded CT data in combination with the plantar pressure measurements. Gait analysis data will be used to drive the models and in combination with the 3D surface scans for scaling purposes. Predicted plantar pressures and muscle activation patterns predicted from the models will be compared to determine the validity of the models.DiscussionThis protocol will lead to the generation of unique datasets which will be used to develop linked inverse dynamic and forward dynamic biomechanical foot models. These models may be beneficial in predicting the effect of and thus improving the efficacy of orthotic devices for the foot and ankle.

Measurement of Walking Ground Reactions in Real-Life Environments: A Systematic Review of Techniques and Technologies

“…The key sources of errors in estimating , and signals for each class of methods are: Kinematics-based methods: (1) these methods rely on a dynamic human model to estimate , and signals. It has been shown that the accuracy of the estimated signals is very sensitive to the characteristics of the human model such as foot [ 106 ] and knee joint [ 107 ] models. This can be a source of significant uncertainty in the accuracy of the model outputs; (2) errors in measured kinematic data, particularly errors in the measured orientations in the case of using wearable IMUs [ 108 ]; (3) the simplifying assumptions used in body dynamic model and the inverse dynamics analysis, such as solid body segments and frictionless joints; (4) the inaccuracies in anthropometric data, particularly the size, density and weight of body segments, the location of joint centres and the location of centre of mass of each body segment; (5) soft tissue artefacts (STA) [ 109 , 110 ]; and (6) inherent computational errors of the methods proposed to solve the indeterminacy problem of the closed-kinematic chain during DSP.…”

What Has Finite Element Analysis Taught Us about Diabetic Foot Disease and Its Management? A Systematic Review

“…Presently, the generation of an anatomically detailed 3D model of a foot from imaging data is a time and labour intensive process and is not feasible for individual patients. Approaches using template models that can be parametrically scaled to match the foot anatomy of different individuals based on simpler measurements have been suggested [48] . This may be a more feasible approach but it remains to be fully realised.…”

The Glasgow‐Maastricht foot model, evaluation of a 26 segment kinematic model of the foot

“…Detailed information on the data capturing of the measurements in this article have been published before [ 15 ]. This section gives a brief overview of the measurements performed to acquire input data for the kinematic model.…”

“…The model was driven using motion capture data from all participants, three trials for each subject. A previously described marker protocol with 43 markers on the lower extremities was used [ 15 ]. The marker data was used to calculate joint angles in a kinematic analysis of an over-determinate system [ 17 ].…”