Neuromusculoskeletal model calibration accounts for differences in electromechanical delay and maximum isometric muscle force.
J Biomech
; 149: 111503, 2023 03.
Article
em En
| MEDLINE
| ID: mdl-36842407
Electromechanical delay (EMD) and maximum isometric muscle force (FoM) are important parameters for joint contact force calculation with EMG-informed neuromusculoskeletal (NMS) models. These parameters can vary between tasks (EMD) and individuals (EMD and FoM), making it challenging to establish representative values. One promising approach is to personalise candidate parameters to the participant (e.g., FoM by regression equation) and then adjust all parameters within a calibration (i.e., numerical optimisation) to minimise error between corresponding pairs of experimental measures and model-predicted values. The purpose of this study was to determine whether calibration of an NMS model resulted in consistent joint contact forces, regardless of EMD value or personalisation of FoM. Hip, knee, and ankle contact forces were predicted for 28 participants using EMG-informed NMS models. Differences in joint contact forces with EMD were examined in six models, calibrated with EMD from 15 to 110 ms. Differences in joint contact forces with personalisation of FoM were examined in two models, both calibrated with the same initial EMD (50 ms), one with generic and one with personalised values for FoM. For all models, joint contact force peaks during the first and second halves of stance were extracted and compared using a repeated-measures analysis of variance. Calibrated models with EMD set between 35 and 70 ms produced similar magnitude and timing of peak joint contact forces. Compared with generic values, personalising and then calibrating FoM resulted in comparable peak contact forces at hip, but not knee or ankle, while also producing muscle-specific tensions similar to reported literature. Overall, EMD between 35 and 70 ms and personalised initial values of FoM before calibration are advised for EMG-informed NMS modelling.
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2023
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Article