Assessment of residual reduction procedures for high-speed tasks

Abstract

Background: Experimental and modeling errors can lead to dynamically inconsistent results when performing inverse dynamic analyses of human movement. Adding low-value residual pelvis actuators could deal with such a problem. However, in certain tasks, these residuals may remain quite large, and strategies based on motion or force variation must be applied. Research question: Can the dynamic inconsistency be handled by an optimal control algorithm that changes the measured kinematics in the preparatory phase of the single leg triple hop test, a relatively high-speed and torque-demanding task, so that residuals are kept within a low range? Methods: The proposed optimal control algorithm was developed as a tracking problem, in which the implicit form of dynamics was used. Equations of motion were introduced as path constraints, as well as residual forces and moments acting on the pelvis. To do so, GPOPS-II and IPOPT were employed to solve the optimization problem. Furthermore, OpenSim API was called at each iteration to solve the equations of motion through an inverse dynamic analysis. Results: Results presented a high reduction in all six components of residual actuators during the entire task. Moreover, resulting motion after the optimization showed a very similar evolution than the reference motion before the ascending phase of the task. Once the ascending phase started, some coordinates presented a more significant discrepancy compared to the reference, such as the pelvis tilt and lumbar extension. Significance: The findings suggest that the proposed algorithm can deal with dynamic inconsistency in high-speed tasks, obtaining low residual forces and moments while keeping similar kinematics. Hence, it could complement other optimal control algorithms that simulate new motions, relying on dynamically consistent data.

Three-dimensional data-tracking simulations of sprinting using a direct collocation optimal control approach

“…It is not uncommon to obtain large dynamic inconsistencies in the form of pelvis residual forces and moments that surpass 1,000 N and 300 Nm, respectively, when performing a standard IDA within sprinting (Aeles et al, 2018). The approach we have used in this study builds on work of other studies (Lin & Pandy, 2017;Pallarès-López et al, 2019) who demonstrated the ability of the direct collocation optimal control approach to reduce residuals within sporting tasks (hopping and running). In this study we demonstrated that it is possible to use this approach to generate dynamically consistent motions in a demanding task that spanned all three planes of motion.…”

“…These residuals are further exacerbated during explosive tasks, such as sprinting, where experimental errors and modelling assumptions are likely to become more critical. Methods such as the residual reduction algorithm (RRA) within OpenSim (Delp et al, 2007) and optimal control approaches (Lin & Pandy, 2017;Meyer et al, 2016;Pallarès-López et al, 2019) have been introduced to compensate for the residuals, although they have not seen widespread adoption within the sports biomechanics literature. Furthermore, within the sports biomechanics literature these residuals are typically neglected, raising questions on the errors in IDA and the validity of the corresponding findings.…”

“…To conduct the evaluation step, data-tracking simulations using optimal control theory can be performed (Umberger & Miller, 2017), as they provide the opportunity to quantitatively determine how a modelling and simulation framework performs at reproducing experimental data. In addition, a major benefit of optimal control based data-tracking simulations is that they provide an elegant approach to improve the dynamic consistency of a simulation by either minimising or constraining the residuals, particularly when used with the direct collocation method (Lin & Pandy, 2017;Meyer et al, 2016;Pallarès-López et al, 2019). To date, however, no study has attempted to use this approach within a highly demanding sporting movement, such as sprinting.…”

The quest for dynamic consistency: a comparison of OpenSim tools for residual reduction in simulations of human running

“…While benchmarks exist for acceptable levels of residuals [1], there are no guidelines on whether these benchmarks are achievable with a single RRA iteration, or whether a set number of RRA iterations is required. Lastly, there are no studies determining whether OpenSim's RRA tool offers comparable residual reduction to other approaches in the literature [2][3][4][5][6] or whether new tools [13,14] may outperform this.…”

“…The issue of dynamic inconsistency has led researchers to develop various formulaic- [2] and optimization-based [3][4][5][6] approaches to reduce or eliminate residuals from biomechanical data. These works [2][3][4][5][6] have all demonstrated a capacity to reduce residuals to a minimal level, yet require substantial manual implementation of a multibody system model. OpenSim [7] is a widely used software that aims to simplify the process of modelling and simulating multibody systems to a semi-automated level.…”