Estimation of trunk mechanical properties using system identification: Effects of experimental setup and modelling assumptions

Babak Bazrgari, Maury A. Nussbaum, Michael L. Madigan

Research output: Contribution to journalArticlepeer-review

13 Scopus citations

Abstract

The use of system identification to quantify trunk mechanical properties is growing in biomechanics research. The effects of several experimental and modelling factors involved in the system identification of trunk mechanical properties were investigated. Trunk kinematics and kinetics were measured in six individuals when exposed to sudden trunk perturbations. Effects of motion sensor positioning and properties of elements between the perturbing device and the trunk were investigated by adopting different models for system identification. Results showed that by measuring trunk kinematics at a location other than the trunk surface, the deformation of soft tissues is erroneously included into trunk kinematics and results in the trunk being predicted as a more damped structure. Results also showed that including elements between the trunk and the perturbing device in the system identification model did not substantially alter model predictions. Other important parameters that were found to substantially affect predictions were the cut-off frequency used when low-pass filtering raw data and the data window length used to estimate trunk properties.

Original languageEnglish
Pages (from-to)1001-1009
Number of pages9
JournalComputer Methods in Biomechanics and Biomedical Engineering
Volume15
Issue number9
DOIs
StatePublished - Sep 2012

Bibliographical note

Funding Information:
This work was supported with Cooperative Agreement Number R01OH008504 by the Centers for Disease Control and Prevention (CDC). Its contents are solely the responsibility of the authors and do not necessarily represent the official views of the CDC. The authors dedicate this work to the memory of Dr Kevin P. Granata whose original ideas formed the foundation of the current investigation. The authors would also like to thank K. Muslim, B. Hendershot and N. Toosizadeh for their assistance in data collection, and R. Waldron and W. Vest for their efforts in building the equipment used during the experiment.

Keywords

  • neuromuscular control
  • system identification
  • trunk mechanical properties

ASJC Scopus subject areas

  • Bioengineering
  • Biomedical Engineering
  • Human-Computer Interaction
  • Computer Science Applications

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