A study of plantar stresses underneath metatarsal heads in the human foot 5

CHAPTER CONCLUSIONS ~ There is a wisdom of the head, and a wisdom of the heart~ Charles Dickens 117 5.1 Conclusion This study explored a sophisticated computational model of human foot using musculoskeletal FE modeling, to investigate forefoot plantar stresses underneath MTHs. A 3-D human foot FE model with detailed anatomy was constructed to study the foot mechanism of muscular control, internal joint movements, and plantar stress distributions in three-dimensions. Mechanical responses of the foot’s soft tissue were specifically collected by using an instrumented tissue tester and the material hyperelasticity were determined for the plantar soft tissue under the MTHs. Experimental validation was conducted by a novel gait platform system that is capable of measuring the vertical and shear force components acting at local MTHs during walking. It was found that, with accurately quantified tissue property, muscular loading characteristics, and foot’s geometric positioning, a realistic stress response during foot-ground interactions can be reproduced. The unique joint-angle-dependent tissue responses obtained from underneath an individual MTH provide more accurate and realistic mechanical characterization of the plantar soft tissue property in the forefoot. The forcedisplacement curve and force relaxation behavior produced, pertinent to the foot geometry and loading regime applied to the foot model, has the potential to provide insights into the mechanical behavior of forefoot tissues. An important feature of this tissue tester is that the tester alone is generally applicable for exploration of (joint-angle-dependent) tissue property as an indicator of disease states and risks, such as ulcer formation at the MTH region in neuropathic 118 diabetic feet. These data collected was used in this study for extraction of the hyperelastic material constants of the sub-MTH soft tissue. By transforming the uni-axial stress (σ)–stretch (λ) equations of the Ogden model into contact equations, the material constants can be directly extracted. The material properties of the sub-MTH tissue determined presently were in between those published results of the skin and fat tissue of human heel pad. This could be explained by the fact that only single a homogeneous lumped tissue volume was used to model such tissue, and that material difference between the skin and fat pad had been weighted. And the use of such patient-specific lumped tissue property input for the 3-D foot FE model appears to produce reasonable accurate plantar contact stresses. The dynamic in vivo plantar forces obtained underneath MTHs during gait allows regional interfacial contact stresses to be calculated between the foot and its support surface. The peak sub-MTH shear stresses were quantified. The shear readings correlate well with existing data in the literature. The threedimensional contact stresses predicted at sub-MTH areas of forefoot by the model that interacts with a highly deformable foam pad is in agreement the present measurements as well as previous observations in terms of its magnitude and distributions following heel rise. Based on the simulation results, it was found that plantar shear stresses varied its distribution throughout the domain. A model with specific frictional interactions, based on actual calculated local shear traction ratio, can reproduce the pattern of regional shear distribution at plantar surface. 119 The model sensitivity study predicted the adaptive changes of the foot mechanism, in terms of internal joint configurations and plantar loads distributions, due to reduced muscle effectiveness in G-S complex. The simulation results correspond well with clinical observations in diabetic patients following tendo-Achilles lengthening procedures. Pressure reductions at individual MTHs could be site-specific and possibly dependent on foot structures, such as intrinsic alignment of the metatarsals. These highlighted the clinical relevance of the model in analyzing the foot mechanism. Inclusion of a metatarsal support into the foam pad for enhanced forefoot (i.e. sub-MTH areas) plantar stress relief requires more technical efforts. Plantar pressure distributions were very sensitive to the metatarsal support’s placement as well as its material selection. Based on the simulation results, an additional soft metatarsal support placed at 12 mm proximal to the 2nd MTH helped to reduce local peak pressure compared to using soft foam pad alone. However, placing a stiffer metatarsal support just underneath the 2nd MTH could cause local increase in peak pressure at forefoot plantar surface. The current FE model provides an efficient computational tool to investigate the efficacy of certain design variables used in therapeutic footwear, and also, the model has potential for three-dimensional contact stress analysis at foot-shoe interface. 5.2 Original Contributions The results of this present study may have significant impact on both understanding the three-dimensional plantar stresses tensor, and providing a 120 useful tool for effective evaluation of existing or the development of new ‘Offloading’ techniques at the foot-support interface for sub-MTH stress relief. This thesis examines both plantar pressure and shear stress distributions at plantar surface of the foot experimentally and analytically. In terms of experimental work, an instrumented indentation device was developed to quantify material characteristics of the sub-MTH soft tissue. Also, an integrated gait platform system, incorporating a customized sensor array and high-speed photogrammetry, was designed, fabricated, and calibrated to measure the dynamic interfacial stresses underneath individual metatarsal heads during gait. This provided valuable data for verification of such a sophisticated musculoskeletal foot FE model. A series of parametric modeling analysis was conducted to highlight potential implications of specific muscle force variations on forefoot stress redistribution. The validated model was further demonstrated as a basic tool for possible applications in studying the influence of therapeutic interventions using metatarsal support on plantar forefoot stress redistributions. 5.3 Future directions  The analysis was performed in the model with a homogeneous mass of plantar soft-tissue underneath MTHs. The tissue stress values were only extracted from the soft-tissue boundary, i.e. contact stress distributions at the plantar surface. A more adequate integration of the “true” internal structures of the plantar soft-tissue, such as the one recently presented in the 54th Orthopaedic Research Society (ORS) by Cavanagh et al., (2009), 121 with layered sections of skin, plantar fat pad, and muscle, might help in the future to clarify for example internal tissue trauma among different levels more precisely.  During walking, the time-dependent properties of the soft tissue may affect the stress response of the foot for various phases during gait. Advanced material models that include hyperelasticity and viscoelasticity may be used in the future dedicated to improving the current model. Such models could potentially be calibrated separately using the current instrumented indentation device, or other possible techniques that address both tissue elastic as well as time-dependent behaviors.  The current model only considered the flexor muscle forces for Tibialis posterior, Flexor hallucis longus, Flexor digitorum longus, Peroneus brevis, and Peroneus longus, other than the Achilles tendon. For stance phase gait simulation (i.e. heel strike to toe off), modeling of the extensors was necessary. Future simulation studies should consider using both flexors and extensors when applying muscular loads. Fig. 5.3.1.1. FE mesh of a musculoskeletal foot model with flexors and extensors for stance phase gait simulation 122  The model was validated against the novel gait platform system at patientspecific level. However, the system is subjected to limitations such as the relatively small sensor array size, which requires targeted walking in order to take specific measurements at each MTHs. Future studies may consider expanding the number of sensors used in the gait platform that should allow large scale experimental investigations to be performed. The schematic diagram of such ‘next generation’ force platform system is in Fig. 5.3.1.2. Push-off Heel Strike Walkway Customized force plate Sensors Pit cover Mounting Plate Fig. 5.3.1.2. A future gait platform system with a larger sensor array can be installed in a typical gait lab for large-scale experiments  Application of the current model in design of therapeutic footwear is only preliminary. Analysis of other design factors such as custom-molded insole, arch profiles, wedged shoe soles and variable-stiffness shoe soles may also equally applicable. 123 Appendix A: Finite element analysis (FEA) Finite element analysis is a numerical based method; the basic idea is that rather than obtaining an exact algebraic solution of the governing partial differential equations throughout the domain of interest, one instead numerically solves a system of simultaneous equations that arise from enforcing those governing equations for an array of discrete simplified sub-domains (known as elements). Within these individual elements, specific interpolation basis functions (usually polynomials) are assumed, from which continuous internal variables (e.g., strains) are piecewise approximated on the basis of corresponding parameters (e.g., displacements, in the case of strain) evaluated at a discrete number of characteristic local points (known as nodes). Although the theory of FEA is rather complicated, below is a code written in MATLAB to solve the 2-D Helmholtz equation using the Galerkin finite element method. The basic concept of FEA as numerical approximation techniques was demonstrated. The following MATLAB code is provided: 1. “Main.m” contains code to generate meshes at different resolutions and to generate the boundary conditions described above along with some necessary initializations (including Gaussian quadrature points and weights). The mesh resolution can be changed through the “elemsPerSide” variable. 2. “psi.m” contains code to evaluate bilinear Lagrange basis functions and their derivatives, and should not need modification. 3. “dxiIdxJ.m” is designed to calculate the transformation Jacobian and the term gu(i,j) =(dxi_i/dx_k)*(dxi_j/dx_k). %====================================================== 124 % Program to solve 2D Helmholtz equation using Galerkin % FEM % by CHEN Wenming %====================================================== clear all; clc; %====================================================== % Set up the mesh % % numNodes = total number of global nodes % nodePos = each row is (x,y), row number is the node number % numElems = total number of global elements % elemNode = each row gives the four nodes for each element % in order, the row number is the element number % BCs = boundary conditions (type,value). % Type = essential (displacement) % Type = natural (gradient) %====================================================== ksq = 1; elemsPerSide = 32; sideLength = 8; nodesPerSide = elemsPerSide+1; incr = sideLength/elemsPerSide; nodesPerElement = 4; numNodes = nodesPerSide * nodesPerSide; numElems = elemsPerSide * elemsPerSide; nodePos(1:numNodes,2) = 0; elemNode(1:numElems,4) = 0; BCs(1:numNodes,2) = 0; % This is the u matrix initialization ( k*u = f) u(numNodes) = 0; %====================================================== % Generate nodes %====================================================== n = 1; for j = 1:nodesPerSide for i = 1:nodesPerSide nodePos(n,1) = (i-1)*incr; nodePos(n,2) = (j-1)*incr; if( i == ) BCs(n,1) = 1; BCs(n,2) = 1; u(n) = BCs(n,2); elseif( i == nodesPerSide ) BCs(n,1) = 1; BCs(n,2) = 0; u(n) = BCs(n,2); 125 else BCs(n,1) = 2; BCs(n,2) = 0; end n = n + 1; end end %====================================================== % Generate elements %====================================================== e = 1; for j = 1:elemsPerSide for i = 1:elemsPerSide elemNode(e,1) = (j-1)*nodesPerSide+i; elemNode(e,2) = elemNode(e,1)+1; elemNode(e,3) = elemNode(e,1)+nodesPerSide; elemNode(e,4) = elemNode(e,1)+nodesPerSide+1; e = e + 1; end end %====================================================== % This initialization is for the Stiffness matrix and % pi, dpibydxi1 and dpibydxi2. %====================================================== % This is the pi matrix. pi = 0; % This is the Dpi/Dxi1 matrix. pi1 = 0; % This is the Dpi/Dxi2 matrix. pi2 = 0; % This is the matrix corresponding to first part of LHS in derivation. stiff1(1:4,1:4) = 0; % This is the matrix corresponding to second part of LHS in derivation. stiff2(1:4,1:4) = 0; % This is the matrix that calculates Dxi1/Dx, Dxi2/Dx, Dxi1/Dy and Dxi2/Dy. result(1:2,1:2) = 0; % This is the Jacobian matrix Jacobi = 0; % This is the Element Stiffness matrix. ES(1:4,1:4) = 0; % This matrix derivation gu(1:4) = 0; is to calculate section in first part of LHS in 126 % This is the matrix that contains the function PSI value for each of the % Gauss points. value(:,:) = 0; % This corresponds to the four basis functions. numerator = 4; denominator = 4; % This is the Global stiffness Matrix. GM(1:numNodes,1:numNodes) = 0.0; % This is the Element Stiffness matrix. ES(1:nodesPerElement,1:nodesPerElement) = 0.0; %====================================================== % Set up the numerical integration points 'gaussPos' % and weights 'gaussWei' (2x2) %====================================================== numGaussPoints = 4; % 2x2 gp1 = 0.5 - ( / ( * sqrt( ))); gp2 = 0.5 + ( / ( * sqrt( ))); gaussPos = [ gp1 gp2 gp1 gp2 gp1; gp1; gp2; gp2 ]; gaussWei = [ 0.25; 0.25; 0.25; 0.25 ]; %====================================================== % Initialise the global matrix system K*u=f %====================================================== K(1:numNodes,1:numNodes) = 0.0; f(1:numNodes) = 0.0; f = f'; % THIS IS TO CALCULATE PI(N) , DPIBYDXI1 AND DPIBYDXI2. % These matrices are 4x4 in nature. These matrices contains the values for % the basis points at the four Gaussian points. for j = 1:numerator for h = 1:numGaussPoints der = 0; num = j; 127 xi1 = gaussPos(h,1); xi2 = gaussPos(h,2); pi(j,h) = psi (num, der, xi1, xi2 ); der = 1; pi1(j,h) = psi (num, der, xi1, xi2 ); der = 2; pi2(j,h) = psi (num, der, xi1, xi2 ); end end %==================================== % Create the element stiffness matrix %==================================== %*** Q. Write code here to make the %*** element stiffness matrix, ES % Initialise element stiffness (ES) % Loop over elements for elem = 1:numElems ES(:,:) = 0; stiff1(:,:) = 0; stiff2(:,:) = 0; % This step is to populate x and y values. for k = 1:4 v = elemNode(elem,k); dx(k) = nodePos(v,1); dy(k) = nodePos(v,2); end % This paragraph calculates the Jacobian and the gu matrix. for p = 1:numGaussPoints xi1 = gaussPos(p,1); xi2 = gaussPos(p,2); value1 = 0; value2 =0; result(:,:) = 0; % This step calculates the values of dx/dxi1, dx/dxi2, dy/dxi1 and % dy/dxi2 for the four Gauss points. for q = 1:numerator 128 value1 = psi(q,1,xi1,xi2); value2 = psi(q,2,xi1,xi2); result(1,1) result(1,2) result(2,1) result(2,2) = = = = result(1,1) result(1,2) result(2,1) result(2,2) + + + + ( ( ( ( value1*dx(q) value2*dx(q) value1*dy(q) value2*dy(q) ); ); ); ); end % This step calculates Jacobian value. Jacobi = det(result); % This step calculates gu. ku = inv(result); kt = (ku)'; gu = ku * kt; % This is to calculate the Element Stiffness matrix. for x = 1:numerator for y = 1:denominator First = pi1(x,p)*pi1(y,p)*gu(1,1); Second = pi1(x,p)*pi2(y,p)*gu(1,2); Third = pi2(x,p)*pi1(y,p)*gu(2,1); Four = pi2(x,p)*pi2(y,p)*gu(2,2); stiff1(x,y) = stiff1(x,y) + 0.25 * Jacobi * (First + Second + Third + Four); stiff2(x,y) = stiff2(x,y) + 0.25 * (pi(x,p)*pi(y,p)) * Jacobi; end end end stiff3 = ksq*stiff2; ES = stiff1 - stiff3; %========================================== % Assemble into the global stiffness matrix %========================================== %*** Q. Write code here to assemble this ES %*** into the global stiffness matrix, GM a b c d = = = = elemNode(elem,1); elemNode(elem,2); elemNode(elem,3); elemNode(elem,4); 129 GM(a,a) GM(a,b) GM(a,c) GM(a,d) GM(b,a) GM(b,b) GM(b,c) GM(b,d) GM(c,a) GM(c,b) GM(c,c) GM(c,d) GM(d,a) GM(d,b) GM(d,c) GM(d,d) = = = = = = = = = = = = = = = = GM(a,a) GM(a,b) GM(a,c) GM(a,d) GM(b,a) GM(b,b) GM(b,c) GM(b,d) GM(c,a) GM(c,b) GM(c,c) GM(c,d) GM(d,a) GM(d,b) GM(d,c) GM(d,d) + + + + + + + + + + + + + + + + ES(1,1); ES(1,2); ES(1,3); ES(1,4); ES(2,1); ES(2,2); ES(2,3); ES(2,4); ES(3,1); ES(3,2); ES(3,3); ES(3,4); ES(4,1); ES(4,2); ES(4,3); ES(4,4); end %elements %========================== % Apply boundary conditions %========================== %*** Q. Write code here to apply the boundary %*** conditions to K. You can use any method %*** but may find overwriting the rows of K easiest. %*** %*** This method finds rows that has known boundary conditions and adjusts the values. for n = 1:numNodes if BCs(n,1) == GM(n,1:numNodes) = 0; GM(n,n) = 1; f(n) = BCs(n,2); end end %*** This method adjusts the value of load vector f. for n = 1:numNodes if BCs(n,1) == for z = 1:numNodes f(z) = f(z) - GM(z,n)*BCs(n,2); end f(n) = BCs(n,2); end end %*** %*** This method removes the rows and columns passing the daigonal elements with known values. for n = numNodes:-1:1 if BCs(n,1) == 130 GM(n,:) = []; GM(:,n) = []; f(n) = []; u(n) = []; end end %====================================================== % Solve %====================================================== u = GM \ f; u1(1:numNodes) = 0; % This method is to properly populate te u1 vector. n = 1; t = 1; for j = 1:nodesPerSide for i = 1:nodesPerSide if( i == ) BCs(n,1) = 1; BCs(n,2) = 1; u1(n) = BCs(n,2); elseif( i == nodesPerSide ) BCs(n,1) = 1; BCs(n,2) = 0; u1(n) = BCs(n,2); else u1(n) = u(t); t = t + 1; end n = n + 1; end end % Rearrange solution as 2D array for surface plot n = 1; for j = 1:nodesPerSide for i = 1:nodesPerSide soln(i,j) = u1(n); n = n + 1; end end surf(soln) % Point to look at is x=1.6 y=2.4 x = 1.6; y = 2.4; % This step calculates the reminder of dividing x and y by incr. x1 = mod(x,incr); y1 = mod(y,incr); 131 % This step is to calculate element in which given values of x & y are % calculated. x2 = (x - x1); y2 = (y - y1); node(1:4) = 0; for n = 1:numNodes if (nodePos(n,1) == x2 && nodePos(n,2) == y2) break; end end for e = 1:numElems if ( elemNode(e,1) == n) node(1) = elemNode(e,1); node(2) = elemNode(e,2); node(3) = elemNode(e,3); node(4) = elemNode(e,4); break; end end x3(1:4) = 0; y3(1:4) = 0; for g = 1:4 r = 0; r = node(g); x3(g) = nodePos(r,1); y3(g) = nodePos(r,2); end xi_1 = ( x - x3(1) )/( x3(2) - x3(1) ); xi_2 = ( y - y3(1) )/( y3(3) - y3(1) ); % This step is to calculate the interpolated value at x=1.6, y=2.4. final = 0; si = 0; val = 0; for num = 1:4 si = psi (num, 0, xi_1, xi_2 ); val = u(node(num)); final = final + si * val ; end 132 References Abuzzahab Jr, F. 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Biomechanical assessment of plantar foot tissue in diabetic patients using an ultrasound indentation system. Ultrasound Med Biol 26, 451-6. 140 Vita CHEN Wenming received his double Bachelor's degrees in Optomechatronics and Bioengineering from Huazhong University of Science & Technology and Central China Normal University, in 2004, respectively. He studied further and obtained his Master degree in Orthopedic Biomechanics from INJE University of Korea in 2006 before he came to National University of Singapore for Ph.D. study. His current research work is mainly focused on biomechanical studies on load-bearing soft tissue associated with musculoskeletal disorders. Publications arising from the thesis  Original Research Articles 1. Chen WM, Shim V, Park SB, Lee T, An instrumented tissue tester for measuring soft tissue property under the metatarsal heads in relation to metatarsophalangeal joint angle. J Biomech, 2011. [doi:10.1016/j.jbiomech.2011.03.031] 2. Chen WM, Lee PVS, Park SB, Lee SJ, Lee T, A novel gait platform to measure isolated plantar metatarsal forces during walking. J Biomech, 43(10): 2017–2021, 2010. 3. Chen WM, Lee T, Lee PVS, Lee JW, Lee SJ, Effects of internal stress concentrations in plantar soft-tissue—A preliminary three-dimensional finite element analysis. Med Eng & Phys, 32(4): 324–331, 2010. 4. Chen WM, Lee PVS, Lee T, Plantar soft-tissue stress states in standing: a three-dimensional finite element foot modeling study, Korean J Sport Biomech, 19(2):197-204, 2009. 5. Chen WM, Lee PVS, Shim V, Lee T, Direct determination of toe flexor muscle forces based on sub-metatarsal/toe pad load sharing by using finite element method. Clin Biomech (submitted) 6. Chen WM, Shim V, Park SB, Lee SJ, Lee T, Three-dimensional finite element analysis of the musculoskeletal foot mechanism – role of the gastrocnemius-soleus muscle complex. J Biomech, (submitted)  Podium Presentations at International Conferences 1. Chen WM, Lee PVS, Lee T: Finite Element Model of the Human FootAnkle Joint Complex Validated with Patient-Specific Data. 54th Annual Meeting of the Orthopaedic Research Society, San Francisco, USA, 2008. 141 2. Chen WM, Lee PVS, Shim V P-W, Park SB, Lee SJ, Lee T: Direct determination of toe flexor muscle forces based on sub-MTH/toe pad load sharing by using finite element method. 2nd Congress of the International Foot and Ankle Biomechanics Community, University of Washington, Seattle, USA, 2010. 3. Chen WM, Park SB, Lee T: A novel gait platform for simultaneous measurement of vertical and shear force at local metatarsal site in walking. 56th Annual Meeting of the Orthopaedic Research Society, USA, 2010. 4. Chen WM: Development of a Biomechanical Model of the Foot Complex for the Prevention and Management of Neuropathic Diabetic Foot Ulcers, Singapore Podiatry Symposium: Feet for Life, Singapore, 2009. 5. Chen WM, Lee T, Lee PVS, Lee JW, Lee SJ: Development of a closedchain 3D finite element foot-ankle model - biomechanical perspective on forefoot plantar stress redistribution following Tendo-Achilles Lengthening. Proceedings of 6th World congress on biomechanics, Singapore, 2010. 6. Chen WM, Shim V P-W, Park SB, Lee T: Method for local assessment of plantar shear forces at sub-metatarsal pad/ground interface in walking. Proceedings of 6th World congress on biomechanics, Singapore, 2010. 7. Chen WM, Lee PVS, Shim V P-W, Park SB, Lee SJ, Lee T: Assessment of Sub-metatarsal Pad Elasticity in vivo in Relation to Gait. 57th Annual Meeting of the Orthopaedic Research Society, Long Beach, USA, 2011.  Abstracts Accepted by Upcoming Conferences 8. Chen WM, Shim V P-W, Park SB, Lee T: Three-dimensional finite element analysis of the musculoskeletal foot mechanism-role of the gastrocnemius-soleus muscle complex. XXIIIrd Congress of the International Society of Biomechanics, Brussels, 2011 9. Chen WM, Shim V P-W, Park SB, Lee T: Assessment of regional plantar shear forces at sub-MTH pad/foot-supporting interface in walking. Footwear Biomechanics Symposium, Tübingen/Germany, 2011 10. Chen WM, Shim V P-W, Lee T: Three-dimensional finite element analysis of modified foot-supporting interface for unloading metatarsal heads. Footwear Biomechanics Symposium, Tübingen/Germany, 2011 142 [...]... Sanders, A P., Snijders, C J and van Linge, B., 1992 Medial deviation of the first metatarsal head as a result of flexion forces in hallux valgus Foot & ankle 13, 51 5-22 Sharkey, N A. , Ferris, L., Smith, T S and Matthews, D K., 19 95 Strain and loading of the second metatarsal during heel-lift J Bone Joint Surg Am 77, 1 050 -7 Sharkey, N A and Hamel, A J., 1998 A dynamic cadaver model of the stance phase... fore -foot motion during the stance phase of gait Gait Posture 25, 453 -62 Leardini, A. , O'Connor, J J., Catani, F and Giannini, S., 2000 The role of the passive structures in the mobility and stability of the human ankle joint: a literature review Foot Ankle Int 21, 602- 15 Lemmon, D and Cavanagh, P., 1997 Finite element modelling of plantar pressure beneath the second ray with flexor muscle loading Clin... tendon transfer for the treatment of claw toe deformity J Biomech 42, 1697-704 1 35 Gefen, A. , 2002 Stress analysis of the standing foot following surgical plantar fascia release J Biomech 35, 629-37 Gefen, A. , 2003 Plantar soft tissue loading under the medial metatarsals in the standing diabetic foot Med Eng Phys 25, 491-9 Gefen, A. , Megido-Ravid, M., Azariah, M., Itzchak, Y and Arcan, M., 2001 Integration... 328-9 Athanasiou, K A. , Liu, G T., Lavery, L A. , Lanctot, D R and Schenck, R C., Jr., 1998 Biomechanical topography of human articular cartilage in the first metatarsophalangeal joint Clin Orthop Relat Res 269-81 Bojsen-Moller, F and Flagstad, K E., 1976 Plantar aponeurosis and internal architecture of the ball of the foot Journal of Anatomy 121, 59 9-611 Bojsen-Moller, F and Lamoreux, L., 1979 Significance... the Elastic Properties of Plantar Fascia J Bone Joint Surg Am 46, 482-92 Wu, L., 2007 Nonlinear finite element analysis for musculoskeletal biomechanics of medial and lateral plantar longitudinal arch of Virtual Chinese Human after plantar ligamentous structure failures Clin Biomech (Bristol, Avon) 22, 221-9 Yamamoto, N., Hayashi, K., Kuriyama, H., Ohno, K., Yasuda, K and Kaneda, K., 1992 Mechanical properties... 1 956 Aetiology and management of lesions of the feet in diabetes Br Med J 2, 953 -7 Cavanagh, P and Ulbrecht, J S., 2006 What the Practising Clinician Should Know About Foot Biomechanics In: The Foot in Diabetes, 4th Edition Cavanagh, P R., 1999 Plantar soft tissue thickness during ground contact in walking Journal of Biomechanics 32, 623-8 Cavanagh, P R., Simoneau, G G and Ulbrecht, J S., 1993 Ulceration,... indentation J Biomech 39, 1279-86 Fauth, A R., 2002 Biomechanical function of the human tarsometatarsal joint M.S Thesis, The Pennsylvania State University, University Park, PA Ferris, L., Sharkey, N A. , Smith, T S and Matthews, D K., 19 95 Influence of extrinsic plantar flexors on forefoot loading during heel rise Foot Ankle Int 16, 464-73 Field, J S and Swain, M V., 19 95 Determining the mechanical properties... pressures in diabetic foot ulcers Diabetes Care 20, 855 -8 Stokes, I A. , Faris, I B and Hutton, W C., 19 75 The neuropathic ulcer and loads on the foot in diabetic patients Acta Orthop Scand 46, 839-47 Sutherland, D H., Cooper, L and Daniel, D., 1980 The role of the ankle plantar flexors in normal walking J Bone Joint Surg Am 62, 354 -63 Tabor, D., 1948 A simple theory of static and dynamic hardness Proc... M., Cavanagh, P R., Ulbrecht, J S., Gibbons, G W and Karchmer, A W., 1994 Assessment and management of foot disease in patients with diabetes N Engl J Med 331, 854 -60 Carlson, R E., Fleming, L L and Hutton, W C., 2000 The biomechanical relationship between the tendoachilles, plantar fascia and metatarsophalangeal joint dorsiflexion angle Foot Ankle Int 21, 18- 25 Catterall, R C., Martin, M M and Oakley,... Significance of free-dorsiflexion of the toes in walking Acta orthopaedica Scandinavica 50 , 471-9 Boulton, A J., Hardisty, C A. , Betts, R P., Franks, C I., Worth, R C., Ward, J D and Duckworth, T., 1983 Dynamic foot pressure and other studies as diagnostic and management aids in diabetic neuropathy Diabetes Care 6, 26-33 Bowers, A L and Castro, M D., 2007 The mechanics behind the image: foot and ankle pathology . such as intrinsic alignment of the metatarsals. These highlighted the clinical relevance of the model in analyzing the foot mechanism. Inclusion of a metatarsal support into the foam pad for. reasonable accurate plantar contact stresses. The dynamic in vivo plantar forces obtained underneath MTHs during gait allows regional interfacial contact stresses to be calculated between the. photogrammetry, was designed, fabricated, and calibrated to measure the dynamic interfacial stresses underneath individual metatarsal heads during gait. This provided valuable data for verification of such