Neuromusculoskeletal Model Calibration Significantly Affects Predicted Knee Contact Forces for Walking

Abstract

Though walking impairments are prevalent in society, clinical treatments are often ineffective at restoring lost function. For this reason, researchers have begun to explore the use of patient-specific computational walking models to develop more effective treatments. However, the accuracy with which models can predict internal body forces in muscles and across joints depends on how well relevant model parameter values can be calibrated for the patient. This study investigated how knowledge of internal knee contact forces affects calibration of neuromusculoskeletal model parameter values and subsequent prediction of internal knee contact and leg muscle forces during walking. Model calibration was performed using a novel two-level optimization procedure applied to six normal walking trials from the Fourth Grand Challenge Competition to Predict In Vivo Knee Loads. The outer-level optimization adjusted time-invariant model parameter values to minimize passive muscle forces, reserve actuator moments, and model parameter value changes with (Approach A) and without (Approach B) tracking of experimental knee contact forces. Using the current guess for model parameter values but no knee contact force information, the inner-level optimization predicted time-varying muscle activations that were close to experimental muscle synergy patterns and consistent with the experimental inverse dynamic loads (both approaches). For all the six gait trials, Approach A predicted knee contact forces with high accuracy for both compartments (average correlation coefficient r ¼ 0.99 and root mean square error (RMSE) ¼ 52.6 N medial; average r ¼ 0.95 and RMSE ¼ 56.6 N lateral). In contrast, Approach B overpredicted contact force magnitude for both compartments (average RMSE ¼ 323 N medial and 348 N lateral) and poorly matched contact force shape for the lateral compartment (average r ¼ 0.90 medial and À0.10 lateral). Approach B had statistically higher lateral muscle forces and lateral optimal muscle fiber lengths but lower medial, central, and lateral normalized muscle fiber lengths compared to Approach A. These findings suggest that poorly calibrated model parameter values may be a major factor limiting the ability of neuromusculoskeletal models to predict knee contact and leg muscle forces accurately for walking.

Individual muscle contributions to tibiofemoral compressive articular loading during walking, running and sidestepping

“…This is understandable, as implant patients are discouraged from performing such vigorous tasks due to risks to the implant. However model predictions have been consistent with previous literature (Fregly et al, 2012;Fregly et al, 2009), where comparisons were possible, we have shown accurate predictions of joint moments (Lloyd and Besier, 2003) and TFJ contact loads (Gerus et al, 2013;Serrancoli et al, 2016;Walter et al, 2014;Wu et al, 2016).…”

Subject-specific calibration of neuromuscular parameters enables neuromusculoskeletal models to estimate physiologically plausible hip joint contact forces in healthy adults

“…Previous studies involving people with instrumented knee implants (Fregly et al, 2012) have also shown that calibrating the NMS model to the individual is essential in estimating accurate KJCF (Gerus et al, 2013;Serrancolí et al, 2016). Furthermore, tracking experimental KJCF measurements (Serrancolí et al, 2016) or minimising peak KJCF (Gerus et al, 2013) were additional calibration criteria that successfully improved KJCF estimates.…”

Can Measured Synergy Excitations Accurately Construct Unmeasured Muscle Excitations?

“…However, muscle excitations predicted by the 5 synergy excitations were only slightly closer to the 13 experimental muscle excitations than were those predicted by the 44 independent muscle excitations. Serrancol ı et al [35] found 44 muscle excitations that could be closely fit by 5 synergy excitations derived from ten experimental muscle EMG signals collected from a different instrumented knee subject. Neuromusculoskeletal model parameter values were calibrated using a two-level optimization approach, and the calibrated model predicted knee contact and leg muscle forces for walking trials withheld from the calibration process.…”

“…Transactions of the ASME Refs. [27,35]). If the unknown synergy excitations could be obtained from experimentally measured muscle excitations, they could serve as subject-specific basis functions to constrain and simplify the construction of all muscle excitations [26].…”