A challenging aspect of subject specific musculoskeletal modeling is the estimation of muscle parameters, especially optimal fiber length and tendon slack length. In this study, the method for scaling musculotendon parameters published by Winby et al. (2008), J. Biomech. 41, 1682-1688, has been reformulated, generalized and applied to two cases of practical interest: 1) the adjustment of muscle parameters in the entire lower limb following linear scaling of a generic model and 2) their estimation "from scratch" in a subject specific model of the hip joint created from medical images. In the first case, the procedure maintained the muscles׳ operating range between models with mean errors below 2.3% of the reference model normalized fiber length value. In the second case, a subject specific model of the hip joint was created using segmented bone geometries and muscle volumes publicly available for a cadaveric specimen from the Living Human Digital Library (LHDL). Estimated optimal fiber lengths were found to be consistent with those of a previously published dataset for all 27 considered muscle bundles except gracilis. However, computed tendon slack lengths differed from tendon lengths measured in the LHDL cadaver, suggesting that tendon slack length should be determined via optimization in subject-specific applications. Overall, the presented methodology could adjust the parameters of a scaled model and enabled the estimation of muscle parameters in newly created subject specific models. All data used in the analyses are of public domain and a tool implementing the algorithm is available at https://simtk.org/home/opt_muscle_par.
Three-dimensional gait analysis (3DGA) has become a common clinical tool for treatment planning in children with cerebral palsy (CP). Many clinical gait laboratories use the conventional gait analysis model (e.g. Plug-in-Gait model), which uses Direct Kinematics (DK) for joint kinematic calculations, whereas, musculoskeletal models, mainly used for research, use Inverse Kinematics (IK). Musculoskeletal IK models have the advantage of enabling additional analyses which might improve the clinical decision-making in children with CP. Before any new model can be used in a clinical setting, its reliability has to be evaluated and compared to a commonly used clinical gait model (e.g. Plug-in-Gait model) which was the purpose of this study. Two testers performed 3DGA in eleven CP and seven typically developing participants on two occasions. Intra- and inter-tester standard deviations (SD) and standard error of measurement (SEM) were used to compare the reliability of two DK models (Plug-in-Gait and a six degrees-of-freedom model solved using Vicon software) and two IK models (two modifications of 'gait2392' solved using OpenSim). All models showed good reliability (mean SEM of 3.0° over all analysed models and joint angles). Variations in joint kinetics were less in typically developed than in CP participants. The modified 'gait2392' model which included all the joint rotations commonly reported in clinical 3DGA, showed reasonable reliable joint kinematic and kinetic estimates, and allows additional musculoskeletal analysis on surgically adjustable parameters, e.g. muscle-tendon lengths, and, therefore, is a suitable model for clinical gait analysis.
We explored the tibiofemoral contact forces and the relative contributions of muscles and external loads to those contact forces during various gait tasks. Second, we assessed the relationships between external gait measures and contact forces. A calibrated electromyography-driven neuromusculoskeletal model estimated the tibiofemoral contact forces during walking (1.44±0.22ms(-1)), running (4.38±0.42ms(-1)) and sidestepping (3.58±0.50ms(-1)) in healthy adults (n=60, 27.3±5.4years, 1.75±0.11m, and 69.8±14.0kg). Contact forces increased from walking (∼1-2.8 BW) to running (∼3-8 BW), sidestepping had largest maximum total (8.47±1.57 BW) and lateral contact forces (4.3±1.05 BW), while running had largest maximum medial contact forces (5.1±0.95 BW). Relative muscle contributions increased across gait tasks (up to 80-90% of medial contact forces), and peaked during running for lateral contact forces (∼90%). Knee adduction moment (KAM) had weak relationships with tibiofemoral contact forces (all R(2)<0.36) and the relationships were gait task-specific. Step-wise regression of multiple external gait measures strengthened relationships (0.20