Motion-Based Prediction of Hands and Feet Contact Efforts During Asymmetric Handling Tasks

IEEE Trans Biomed Eng. 2020 Feb;67(2):344-352. doi: 10.1109/TBME.2019.2913308. Epub 2019 Apr 25.

Abstract

This paper proposes a method to predict the external efforts exerted on a subject during handling tasks, only with a measure of his motion. These efforts are the contacts forces and moments on the ground and on the load carried by the subject. The method is based on a contact model initially developed to predict the ground reaction forces and moments. Discrete contact points are defined on the biomechanical model at the feet and the hands. An optimization technique computes the minimal forces at each of these points, satisfying the dynamic equations of the biomechanical model and the load. The method was tested on a set of asymmetric handling tasks performed by 13 subjects and validated using force platforms and an instrumented load. For each task, predictions of the vertical forces obtained an RMSE of about 0.25 N/kg for the feet contacts and below 1 N/kg for the hand contacts. L5/S1 joint moments were then computed using the predicted and the measured data. RMSE of 18 Nm and rRMSE below 10% were obtained for the flexion/extension component. In conclusion, this method enables to quantitatively assess asymmetric handling tasks on the basis of kinetics variables without additional instrumentation, such as force sensors, and thus improve the ecological aspect of the studied tasks. This method has a great potential to be applied in work tasks analyses in ergonomics studies or sports gestures analyses involving hand contacts in exercise science.

MeSH terms

  • Adult
  • Ergonomics / methods*
  • Foot / physiology*
  • Hand / physiology*
  • Hand Strength / physiology
  • Humans
  • Male
  • Models, Biological
  • Models, Statistical
  • Movement / physiology*
  • Neural Networks, Computer
  • Young Adult