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Open Access Study protocol

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

Michiel Oosterwaal12, Scott Telfer3*, Søren Tørholm4, Sylvain Carbes4, Lodewijk W van Rhijn1, Ross Macduff5, Kenneth Meijer1 and Jim Woodburn3

Author Affiliations

1 NUTRIM, Department of Human Movement Sciences, Maastricht University Medical Centre +, PO 5800, 6202 AZ Maastricht, The Netherlands

2 CAPHRI, Dep. of Orthopaedic Surgery, Maastricht University Medical Centre +, PO 5800, 6202 AZ Maastricht, The Netherlands

3 School of Health and Life Sciences, Glasgow Caledonian University, Cowcaddens Road, Glasgow, UK

4 AnyBody Technology A/S, Niels Jernes Vej 10, DK-9220 Aalborg East, Denmark

5 Department of Radiology, Glasgow Royal Infirmary, Glasgow, UK

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BMC Musculoskeletal Disorders 2011, 12:256  doi:10.1186/1471-2474-12-256

Published: 10 November 2011

Abstract

Background

Currently, 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/Design

Functional 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.

Discussion

This 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.