Finite Element Modeling Used to Study Stress Distribution on the Foot

A method to study the stress distribution inside the forefoot during walking was developed at the Cleveland Clinic Foundation by a researcher from the NASA Glenn Research Center. In this method, a semiautomated process was outlined to create a three-dimensional, patient-specific, finite element model (FEM) of the forefoot using magnetic resonance images (MRI). The images were processed in Matlab using the k-nearest neighbor (k-NN) classification algorithm and Sobel edge detection to separate the different tissue types: bone, skin, fat, and muscle. This information was used to create curves and surfaces that were exported to an FEM preprocessor known as Truegrid. In Truegrid, eight-noded or brick elements were created by using surface mapping. The FEM was processed and postprocessed in Abaqus. Material properties of the models were obtained from past experiments such as fat pad confined compression, skin axial and biaxial tests, muscle in vivo compressive tests, and reference literature (bone properties). Nonlinear (hyperelastic) material models were used for the skin (epidermis and dermis), fat, and muscles; and a linear elastic model was used for the bones. Muscle activation during walking yielded uncertainties in the muscle material model since contracted muscles are stiffer than relaxed muscles. These uncertainties were resolved by performing a sensitivity analysis of the muscle material properties. The original properties were multiplied by arbitrary factors of 2, 3, 0.5, and 0.33. The strain and stress distributions, as well as the locations of peak values, were similar in all cases. The peak contact pressure P obtained for each case varied with respect to the applied factor f as follows

Simulation of Lower Limb Axial Arterial Length Change During Locomotion

The effect of external forces on axial arterial wall mechanics has conventionally been regarded as secondary to hemodynamic influences. However, arteries are similar to muscles in terms of the manner in which they traverse joints, and their three-dimensional geometrical requirements for joint motion. This study considers axial arterial shortening and elongation due to motion of the lower extremity during gait, ascending stairs, and sitting-to-standing motion. Arterial length change was simulated by means of a graphics based anatomic and kinematic model of the lower extremity. This model estimated the axial shortening to be as much as 23% for the femoropopliteal arterial region and as much as 21% for the iliac artery. A strong correlation was observed between femoropopliteal artery shortening and maximum knee flexion angle (r2=0.8) as well as iliac artery shortening and maximum hip angle flexion (r2=0.9). This implies a significant mechanical influence of locomotion on arterial behavior in addition to hemodynamics factors. Vascular tissue has high demands for axial compliance that should be considered in the pathology of atherosclerosis and the design of vascular implants

Simulation of Lower Limb Axial Arterial Length Change During Locomotion

The effect of external forces on axial arterial wall mechanics has conventionally been regarded as secondary to hemodynamic influences. However, arteries are similar to muscles in terms of the manner in which they traverse joints, and their three-dimensional geometrical requirements for joint motion. This study considers axial arterial shortening and elongation due to motion of the lower extremity during gait, ascending stairs, and sitting-to-standing motion. Arterial length change was simulated by means of a graphics based anatomic and kinematic model of the lower extremity. This model estimated the axial shortening to be as much as 23% for the femoropopliteal arterial region and as much as 21% for the iliac artery. A strong correlation was observed between femoropopliteal artery shortening and maximum knee flexion angle (r2=0.8) as well as iliac artery shortening and maximum hip angle flexion (r2=0.9). This implies a significant mechanical influence of locomotion on arterial behavior in addition to hemodynamics factors. Vascular tissue has high demands for axial compliance that should be considered in the pathology of atherosclerosis and the design of vascular implants