4.4 Article

Analysis of Human Whole-Body Joint Torques During Overhead Work With a Passive Exoskeleton

期刊

IEEE TRANSACTIONS ON HUMAN-MACHINE SYSTEMS
卷 52, 期 5, 页码 1060-1068

出版社

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/THMS.2021.3128892

关键词

Exoskeletons; Task analysis; Estimation; Sensors; Torque; Arms; Europe; Human whole-body joint torque; floating-base estimation; overhead work analysis; upper-limb exoskeleton

资金

  1. EU An.Dy Project
  2. European Union [731540]

向作者/读者索取更多资源

This study found that upper-limb exoskeletons can significantly reduce overall joint effort, provide support at the shoulders, and transfer part of the internal wrenches to the thighs and legs, increasing torques at the leg joints.
Overhead work is classified as one of the major risk factors for the onset of shoulder work-related musculoskeletal disorders and muscle fatigue. Upper-limb exoskeletons can be used to assist workers during the execution of industrial overhead tasks to prevent such disorders. Twelve novice participants have been equipped with inertial and force/torque sensors to simultaneously estimate the whole-body kinematics and the joint torques (i.e., internal articular stress) by means of a probabilistic estimator, while performing an overhead task with a pointing tool. An evaluation has been performed to analyze the effect at the whole-body level by considering the conditions of wearing and not-wearing PAEXO, a passive exoskeleton for upper-limb support during overhead work. Results point out that PAEXO provides a reduction of the whole-body joint effort across the experimental task blocks (from 66% to 86%). Moreover, the analysis along with five different body areas shows that 1) the exoskeleton provides support at the human shoulders by reducing the joint effort at the targeted limbs, and 2) that part of the internal wrenches is intuitively transferred from the upper body to the thighs and legs, which is shown with an increment of the torques at the legs joints. The promising outcomes show that the probabilistic estimation algorithm can be used as a validation metric to quantitatively assess PAEXO performances, paving thus the way for the next challenging milestone, such as the optimization of the human joint torques via adaptive exoskeleton control.

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