Journal article
Efficacy and efficiency of multivariate linear regression for rapid prediction of femoral strain fields during activity
Hamed Ziaeipoor, Saulo Martelli, Marcus Pandy, Mark Taylor
MEDICAL ENGINEERING & PHYSICS | ELSEVIER SCI LTD | Published : 2019
Abstract
Multivariate Linear Regression-based (MLR) surrogate models were explored to reduce the computational cost of predicting femoral strains during normal activity in comparison with finite element analysis. The musculoskeletal model of one individual, the finite-element model of the right femur, and experimental force and motion data for normal walking, fast walking, stair ascent, stair descent, and rising from a chair were obtained from a previous study. Equivalent Von Mises strain was calculated for 1000 frames uniformly distributed across activities. MLR surrogate models were generated using training sets of 50, 100, 200 and 300 samples. The finite-element and MLR analyses were compared usin..
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Awarded by Australian Research Council
Funding Acknowledgements
This work was supported by the Australian Government Research Training Program Scholarship (AGRTPS); and the Australian Research Council (Grant no. DP180103146).