The sensitivity of a lower limb model to axial rotation offsets and muscle bounds at the knee

Abstract

Soft tissue artifacts during motion capture can lead to errors in kinematics and incorrect estimation of joint angles and segment motion. The aim of this study was to evaluate the effect of shank segment axial rotation and knee rotator muscle bounds on predicted muscle and joint forces in a musculoskeletal model of the lower limb. A maximal height jump for ten subjects was analysed using the original motion data and then modified for different levels of internal and external rotation, and with the upper force bound doubled for five muscles. Both externally rotating the shank and doubling the muscle bounds increased the ability of the model to find a solution in regions of high loading. Muscle force levels in popliteus and tensor fascia latae showed statistically significant differences, but less so in plantaris, sartorius or gracilis. The shear and patellofemoral joint forces were found to be significantly affected by axial rotation during specific phases of the motion and were dependent on the amount of rotation. Fewer differences were observed when doubling the muscle bounds, except for the patellofemoral force and plantaris and sartorius muscle force, which were significantly increased in many of the jump phases. These results give an insight into the behaviour of the model and give an indication of the importance of accurate kinematics and subject-specific geometry.

Effects of an 8-week strength training intervention on tibiofemoral joint loading during landing: a cohort study

“… 20 21 One reason for this may be the fact that optical motion capture methodologies are less able to discriminate between differences in internal/external rotation and abduction/adduction than between differences in joint flexion and extension due to the measurement error associated with soft-tissue artefact. 55 In contrast, we have previously shown that the forces predicted by the model employed here are sensitive to small changes in kinematics (in particular, that they are sensitive to small changes in the internal/external rotation of the tibia 43 ). It is thus entirely credible to suggest that musculoskeletal models may be more sensitive to changes in internal kinetics than more traditional approaches are to changes in kinematics.…”

“…The validation and verification of FreeBody has been described previously, 41–44 with a focus on the accuracy of the TF predictions 41 and the sensitivity of the model to the input kinematic data and its muscle force upper bounds. 43 …”

Reliability and Minimal Detectable Change Values for Predictions of Knee Forces during Gait and Stair Ascent Derived from the FreeBody Musculoskeletal Model of the Lower Limb

“…FreeBody is a publicly available musculoskeletal model of the lower limb (Cleather and Bull, 2015 ), the development and validation of which has been described extensively within the literature (Cleather and Bull, 2010a , b , 2011a , b ; Cleather et al, 2011a , b ; Southgate et al, 2012 ; Ding et al, 2016 ; Price et al, 2016 ). In particular, the sensitivity of the model to its assumptions (for instance, the inverse dynamics methodology, the musculoskeletal geometry data set employed, and the degrees of freedom of the joints; Cleather and Bull, 2010a , b , 2011b ) and to measurement error (e.g., error in the measurement of shank segment axial rotation; Southgate et al, 2012 ) have been determined and the predictions of the model during activities of daily living and more dynamic activities have been compared to experimental measurements including electromyography and joint contact forces measured by telemetry from instrumented prostheses (Cleather and Bull, 2015 ; Ding et al, 2016 ; Price et al, 2016 ). However, the inter-session reliability of FreeBody is currently unknown.…”

Neural network based approximation of muscle and joint contact forces during jumping and landing

“…In order to generate the training and test data for this study, a publicly available model of the lower limb (FreeBody) was used to estimate the muscle and joint contact forces exhibited during jumping and landing from the motion capture and force plate data. The development and testing of FreeBody has been previously described in great detail [5,7,[10][11][12][13][14][15][16][17] and so only a brief sketch of the model is provided here. In short, the equations of motion of a chain of 5 rigid segments representing the pelvis and right lower limb are posed using wrench notation.…”