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Heuristic Evaluations of Back-Support, Shoulder-Support, Handgrip-Strength Support, and Sit-Stand-Support Exoskeletons Using Universal Design Principles

Alejandra Martínez‐Monés et al.

IISE Transactions on Occupational Ergonomics and Human Factors2025https://doi.org/10.1080/24725838.2025.2476438article
AJG 1
Weight
0.46

What the paper says

OCCUPATIONAL APPLICATIONSOur study evaluated four occupational exoskeletons using universal design principles, and we found that the exoskeleton design needs improvement to achieve equitable use by diverse worker sets (including disabled, older, and women workers). Assembling exoskeletons for use, donning and doffing wearable devices, and disassembling them can all be difficult because of the strength, dexterity, reach, and balance requirements of users. Workers with disabilities are likely to require additional support from another person to assemble or use these devices. Exoskeleton design can be improved to provide feedback on user actions, error prevention, and recovery. Factors such as assembly and storage space demands, training needs, additional personnel to assist users, and personalization costs could pose substantial barriers in industrial adoption.

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https://doi.org/https://doi.org/10.1080/24725838.2025.2476438

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@article{alejandra2025,
  title        = {{Heuristic Evaluations of Back-Support, Shoulder-Support, Handgrip-Strength Support, and Sit-Stand-Support Exoskeletons Using Universal Design Principles}},
  author       = {Alejandra Martínez‐Monés et al.},
  journal      = {IISE Transactions on Occupational Ergonomics and Human Factors},
  year         = {2025},
  doi          = {https://doi.org/https://doi.org/10.1080/24725838.2025.2476438},
}

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Heuristic Evaluations of Back-Support, Shoulder-Support, Handgrip-Strength Support, and Sit-Stand-Support Exoskeletons Using Universal Design Principles

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Evidence weight

0.46

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.37 × 0.4 = 0.15
M · momentum0.60 × 0.15 = 0.09
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.