Quantifying Human Upper Limb Stiffness Responses Based on a Computationally Efficient Neuromusculoskeletal Arm Model

Maria Sapounaki, Pierre Schumacher, Winfried Ilg, Martin A. Giese, Christophe Maufroy, Andreas Bulling, Syn Schmitt, Daniel F. B. Haeufle, Isabell Wochner

Abstract: Activities of daily living such as drinking and eating can be severely impaired for patients suffering from neurodegenerative diseases. One promising solution are assistive devices that apply corrective forces while still allowing the intended movements. However, real-time estimation of the required forces requires a detailed understanding of the limb's impedance characteristics. Here, we test and validate the stiffness response of a computationally efficient neuro-musculoskeletal arm model and its response to various force perturbations. We demonstrate that the arm model predicts stiffness characteristics that closely match experimental data recorded from humans and presents real-time applicability, allowing for implementation in practical scenarios and. Additionally, we predict the stiffness response for novel force levels and arm configurations. In the future, these predictions could be used to estimate corrective forces for assistive devices in real-time.

External IDs:dblp:conf/biorob/SapounakiSIGMBSHW24