Nonlinear Elastic Material Property Estimation of Lower Extremity Residual Limb Tissues

Document Type




Format of Original

11 p.

Publication Date



Institute of Electrical and Electronics Engineers

Source Publication

IEEE Transactions on Neural Systems and Rehabilitation Engineering

Source ISSN


Original Item ID

doi: 10.1109/TNSRE.2003.810436


The interface stresses between the residual limb and prosthetic socket have been studied to investigate prosthetic fit. Finite-element models of the residual limb-prosthetic socket interface facilitate investigation of the mechanical interface and may serve as a potential tool for future prosthetic socket design. However, the success of such residual limb models to date has been limited, in large part due to inadequate material formulations used to approximate the mechanical behavior of residual limb soft tissues. Nonlinear finite-element analysis was used to simulate force-displacement data obtained during in vivo rate-controlled (1, 5, and 10 mm/s) cyclic indentation of the residual limb soft tissues of seven individuals with transtibial amputation. The finite-element models facilitated determination of an appropriate set of nonlinear elastic material coefficients for bulk soft tissue at discrete clinically relevant test locations. Axisymmetric finite-element models of the residual limb bulk soft tissue in the vicinity of the test location, the socket wall and the indentor tip were developed incorporating contact analysis, large displacement, and large strain, and the James-Green-Simpson nonlinear elastic material formulation. Model dimensions were based on medical imaging studies of the residual limbs. The material coefficients were selected such that the normalized sum of square error (NSSE) between the experimental and finite-element model indentor tip reaction force was minimized. A total of 95% of the experimental data were simulated using the James-Green-Simpson material formulation with an NSSE less than 5%. The respective James-Green-Simpson material coefficients varied with subject, test location, and indentation rate. Therefore, these coefficients cannot be readily extrapolated to other sites or individuals, or to the same site and individual some time after testing.


IEEE Transactions on Neural Systems and Rehabilitation Engineering, Vol. 11, No. 1 (March 2003): 43-53. DOI.