title: Robust identification of multi-joint human arm impedance based on dynamics decomposition: a modeling study.
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.
authors.affiliation: Rehabilitation Institute of Chicago, Chicago, IL 60611, USA. sanghoon.kang@northwestern.edu
authors.forename: Sang Hoon
authors.initials: SH
authors.lastname: Kang
authors.forename: Li-Qun
authors.initials: LQ
authors.lastname: Zhang
mesh_terms: D001132:Arm / Q000502:physiology*; D001696:Biomechanical Phenomena; D017097:Electric Impedance; D006801:Humans; D008962:Models, Theoretical