Modelling three-dimensional human strength capacity: logistic vs. polynomial surface equations
by John M. Looft; Laura A. Frey-Law
International Journal of Human Factors Modelling and Simulation (IJHFMS), Vol. 5, No. 1, 2015

Abstract: One approach to modelling muscle strength is to represent peak torque as three-dimensional (3D) torque-angle-velocity surfaces at the joint level. These nonlinear relationships have been modelled using polynomial equations. However, we hypothesised logistic equations would better represent 3D peak strength based on known 'S-shaped' relationships between torque and velocity. To compare the two approaches, we modelled eight 3D strength surfaces based on previously published data, elbow and knee strength, using polynomial and logistic equations. Both models fit the strength data well, with median R² values of 0.983 and 0.971 for polynomial and logistic equations, respectively. However, when extrapolating the models to a full normal range of motion (0° to 140°) 100% of the polynomial surfaces, but only 25% of the logistic surfaces, displayed non-physiologic strength estimates (i.e., crossed zero). Accordingly, logistic equations may provide equal or better representations of 3D joint strength surfaces for digital human modelling.

Online publication date: Wed, 18-Mar-2015

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