Estimating lumbar spine loading when using back-support exoskeletons in lifting tasks

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Date

2023-01

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Elsevier

Abstract

Low-back pain (LBP) continues as the leading cause of work-related musculoskeletal disorders, and the high LBP burden is attributed largely to physical risk factors prevalent in manual material handling tasks. Industrial back-support exoskeletons (BSEs) are a promising ergonomic intervention to help control/prevent exposures to such risk factors. While earlier research has demonstrated beneficial effects of BSEs in terms of reductions in superficial back muscle activity, limited evidence is available regarding the impacts of these devices on spine loads. We evaluated the effects of two passive BSEs (BackX™ AC and Laevo™ V2.5) on lumbosacral compression and shear forces during repetitive lifting using an optimization-based model. Eighteen participants (gender-balanced) completed four minutes of repetitive lifting in nine different conditions, involving symmetric and asymmetric postures when using the BSEs (along with no BSE as a control condition). Using both BSEs reduced estimated peak compression and anteroposterior shear forces (by ~8-15%). Such reductions, however, were task-specific and depended on the BSE design. Laevo™ use reduced mediolateral shear forces during asymmetric lifting (by ~35%). We also found that reductions in composite measures of trunk muscle activity may not correspond well with changes in spine forces when using a BSE. These results can help guide the proper selection and application of BSEs during repetitive lifting tasks. Future work is recommended to explore the viability of different biomechanical models to assess changes in spine mechanical loads when using BSEs and whether reasonable estimates would be obtained using such models.

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Keywords

Low-Back Pain, Wearable Assistive Devices, Computational Biomechanics, AnyBody™ Modeling System, Musculoskeletal modeling, Prevention, Pain Research, Chronic Pain, Rehabilitation, Bioengineering, Musculoskeletal

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