BackgroundAccurately measuring of intrinsic foot kinematics using skin mounted markers is difficult, limited in part by the physical dimensions of the foot. Existing kinematic foot models solve this problem by combining multiple bones into idealized rigid segments. This study presents a novel foot model that allows the motion of the 26 bones to be individually estimated via a combination of partial joint constraints and coupling the motion of separate joints using kinematic rhythms.MethodsSegmented CT data from one healthy subject was used to create a template Glasgow-Maastricht foot model (GM-model). Following this, the template was scaled to produce subject-specific models for five additional healthy participants using a surface scan of the foot and ankle. Forty-three skin mounted markers, mainly positioned around the foot and ankle, were used to capture the stance phase of the right foot of the six healthy participants during walking. The GM-model was then applied to calculate the intrinsic foot kinematics.ResultsDistinct motion patterns where found for all joints. The variability in outcome depended on the location of the joint, with reasonable results for sagittal plane motions and poor results for transverse plane motions.ConclusionsThe results of the GM-model were comparable with existing literature, including bone pin studies, with respect to the range of motion, motion pattern and timing of the motion in the studied joints. This novel model is the most complete kinematic model to date. Further evaluation of the model is warranted.

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.

Detailed knowledge of the loading conditions within the human body is essential for the development and optimization of treatments for disorders and injuries of the musculoskeletal system. While loads in the major joints of the lower limb have been the subject of extensive study, relatively little is known about the forces applied to the individual bones of the foot. The objective of this study was to use a detailed musculoskeletal model to compute the loads applied to the metatarsal bones during gait across several healthy subjects. Motion-captured gait trials and computed tomography (CT) foot scans from four healthy subjects were used as the inputs to inverse dynamic simulations that allowed the computation of loads at the metatarsal joints. Low loads in the metatarsophalangeal (MTP) joint were predicted before terminal stance, however, increased to an average peak of 1.9 times body weight (BW) before toe-off in the first metatarsal. At the first tarsometatarsal (TMT) joint, loads of up to 1.0 times BW were seen during the early part of stance, reflecting tension in the ligaments and muscles. These loads subsequently increased to an average peak of 3.0 times BW. Loads in the first ray were higher compared to rays 2-5. The joints were primarily loaded in the longitudinal direction of the bone.

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