Model-Based Biomechanical Exoskeleton Concept Optimization for a Representative Lifting Task in Logistics

Int J Environ Res Public Health. 2022 Nov 23;19(23):15533. doi: 10.3390/ijerph192315533.

Abstract

Occupational exoskeletons are a promising solution to prevent work-related musculoskeletal disorders (WMSDs). However, there are no established systems that support heavy lifting to shoulder height. Thus, this work presents a model-based analysis of heavy lifting activities and subsequent exoskeleton concept optimization. Six motion sequences were captured in the laboratory for three subjects and analyzed in multibody simulations with respect to muscle activities (MAs) and joint forces (JFs). The most strenuous sequence was selected and utilized in further simulations of a human model connected to 32 exoskeleton concept variants. Six simulated concepts were compared concerning occurring JFs and MAs as well as interaction loads in the exoskeleton arm interfaces. Symmetric uplifting of a 21 kg box from hip to shoulder height was identified as the most strenuous motion sequence with highly loaded arms, shoulders, and back. Six concept variants reduced mean JFs (spine: >70%, glenohumeral joint: >69%) and MAs (back: >63%, shoulder: >59% in five concepts). Parasitic loads in the arm bracing varied strongly among variants. An exoskeleton design was identified that effectively supports heavy lifting, combining high musculoskeletal relief and low parasitic loads. The applied workflow can help developers in the optimization of exoskeletons.

Keywords: AnyBody Modeling System; activities above shoulder height; assistive systems; ergonomics; exoskeleton; heavy lifting; logistics; manual work; multibody simulation; musculoskeletal modeling.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Biomechanical Phenomena
  • Electromyography
  • Exoskeleton Device*
  • Humans
  • Lifting
  • Shoulder / physiology
  • Shoulder Joint* / physiology
  • Upper Extremity

Grants and funding

This work was supported by the Exolog Project funded by the Bundeswehr (Armed Forces of Germany) under Grant No E/U2Ci/KA225/JF080.