Dynamic-joint-strength-based two-dimensional symmetric maximum weight-lifting simulation: Model development and validation

Ritwik Rakshit, Yujiang Xiang, James Yang

Research output: Contribution to journalArticlepeer-review

4 Scopus citations

Abstract

This article presents an optimization formulation and experimental validation of a dynamic-joint-strength-based two-dimensional symmetric maximum weight-lifting simulation. Dynamic joint strength (the net moment capacity as a function of joint angle and angular velocity), as presented in the literature, is adopted in the optimization formulation to predict the symmetric maximum lifting weight and corresponding motion. Nineteen participants were recruited to perform a maximum-weight-box-lifting task in the laboratory, and kinetic and kinematic data including motion and ground reaction forces were collected using a motion capture system and force plates, respectively. For each individual, the predicted spine, shoulder, elbow, hip, knee, and ankle joint angles, as well as vertical and horizontal ground reaction force and box weight, were compared with the experimental data. Both root-mean-square error and Pearson’s correlation coefficient (r) were used for the validation. The results show that the proposed two-dimensional optimization-based motion prediction formulation is able to accurately predict all joint angles, box weights, and vertical ground reaction forces, but not horizontal ground reaction forces.

Original languageEnglish
Pages (from-to)660-673
Number of pages14
JournalProceedings of the Institution of Mechanical Engineers, Part H: Journal of Engineering in Medicine
Volume234
Issue number7
DOIs
StatePublished - Jul 1 2020

Keywords

  • Lifting
  • dynamic joint strength
  • inverse-dynamics optimization
  • manual material handling
  • maximum weight
  • motion prediction
  • predictive dynamics
  • strength percentile
  • validation

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