Robust identification of multi-joint human arm impedance based on dynamics decomposition: A modeling study

Sang Hoon Kang, Li Qun Zhang*

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Multi-joint/multi-degree of freedom (DOF) human arm impedance estimation is important in many disciplines. However, as the number of joints/DOFs increases, it may become intractable to identify the system reliably. A robust, unbiased and tractable estimation method based on a systematic dynamics decomposition, which decomposes a multi-input multi-output (MIMO) system into multiple single-input multi-output (SIMO) subsystems, is developed. Accuracy and robustness of the new method were validated through a human arm and a 2-DOF exoskeleton robot simulation with various magnitudes of sensor resolution and nonlinear friction. The approach can be similarly applied to identify more sophisticated systems with more joints/DOFs involved.

Original languageEnglish (US)
Title of host publication33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2011
Pages4453-4456
Number of pages4
DOIs
StatePublished - Dec 26 2011
Event33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2011 - Boston, MA, United States
Duration: Aug 30 2011Sep 3 2011

Other

Other33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2011
CountryUnited States
CityBoston, MA
Period8/30/119/3/11

ASJC Scopus subject areas

  • Signal Processing
  • Biomedical Engineering
  • Computer Vision and Pattern Recognition
  • Health Informatics

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