Prediction of ground reaction forces and moments during sports-related movements

Abstract

When performing inverse dynamic analysis (IDA) of musculoskeletal models to study human motion, inaccuracies in experimental input data and a mismatch between the model and subject lead to dynamic inconsistency. By predicting the ground reaction forces and moments (GRF&Ms) this inconsistency can be reduced and force plate measurements become unnecessary. In this study, a method for predicting GRF&Ms was validated for an array of sports-related movements. The method was applied to ten healthy subjects performing, for example, running, a side-cut manoeuvre, and vertical jump. Pearson’s correlation coefficient (\(r\)) and root-mean-square deviation were used to compare the predicted GRF&Ms and associated joint kinetics to the traditional IDA approach, where the GRF&Ms were measured using force plates. The main findings were that the method provided estimates comparable to traditional IDA across all movements for vertical GRFs (\(r\) ranging from 0.97 to 0.99, median 0.99), joint flexion moments (\(r\) ranging from 0.79 to 0.98, median 0.93), and resultant joint reaction forces (\(r\) ranging from 0.78 to 0.99, median 0.97). Considering these results, this method can be used instead of force plate measurements, hereby, facilitating IDA in sports science research and enabling complete IDA using motion analysis systems that do not incorporate force plate data.

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Abbreviations

IDA:

Inverse dynamic analysis

GRF&Ms:

Ground reaction forces and moments

ASP:

Acceleration from a standing position

AMS:

AnyBody Modeling System

DOF:

Degrees-of-freedom

GRF:

Ground reaction force

GRM:

Ground reaction moment

AFM:

Ankle flexion moment

ASEM:

Ankle subtalar eversion moment

KFM:

Knee flexion moment

HFM:

Hip flexion moment

HAM:

Hip abduction moment

HERM:

Hip external rotation moment

JRF:

Joint reaction force

\(r\) :

Pearson’s correlation coefficient

RMSD:

Root-mean-square deviation

RL:

Right leg

LL:

Left leg

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Acknowledgements

This work received funding from the Danish Council for Independent Research under grant number DFF-4184-00018 to M.S. Andersen and from the European Union’s Seventh Framework Programme (FP7/2007–2013) under the LifeLongJoints Project, Grant Agreement no. GA-310477 to M. Jung and M. Damsgaard.

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Correspondence to Michael S. Andersen.

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M. Damsgaard is the head of development, minority shareholder, and member of the board of directors of AnyBody Technology A/S that owns and sells the AnyBody Modeling System.

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Skals, S., Jung, M.K., Damsgaard, M. et al. Prediction of ground reaction forces and moments during sports-related movements. Multibody Syst Dyn 39, 175–195 (2017). https://doi.org/10.1007/s11044-016-9537-4

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Keywords

  • Musculoskeletal model
  • Inverse dynamics
  • Sports science
  • AnyBody Modeling System
  • Force plates