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Journal Articles IEEE Transactions on Human-Machine Systems Year : 2021

Analysis of Human Whole-body Joint Torques during Overhead Work with a Passive Exoskeleton

Abstract

Overhead work is classified as one of the major risk factors for the onset of shoulder work-related musculoskeletal disorders (WMSDs) 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 taskwith 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 5 different body areas shows that i) the exoskeleton provides support at the human shoulders by reducing the joint effort at the targeted limbs and ii) that part of theinternal 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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Dates and versions

hal-03428469 , version 1 (15-11-2021)

Identifiers

Cite

Claudia Latella, Yeshasvi Tirupachuri, Luca Tagliapietra, Lorenzo Rapetti, Benjamin Schirrmeister, et al.. Analysis of Human Whole-body Joint Torques during Overhead Work with a Passive Exoskeleton. IEEE Transactions on Human-Machine Systems, In press, ⟨10.1109/THMS.2021.3128892⟩. ⟨hal-03428469⟩
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