Evidence map›Paper›PMID 39935597›Full record

ArticleWearable technologies2025

From the idea to the user: a pragmatic multifaceted approach to testing occupational exoskeletons.

Christian Di Natali, Tommaso Poliero, Matteo Sposito, Vasco Fanti, Sergio Leggieri, Darwin G Caldwell

Abstract read
In one paragraph

Article in Wearable technologies, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Christian Di NataliDepartment of Advanced Robotics, Istituto Italiano di Tecnologia, XoLab, Genoa, Italy.ORCID https://orcid.org/0000-0001-7399-7399
Tommaso PolieroDepartment of Advanced Robotics, Istituto Italiano di Tecnologia, XoLab, Genoa, Italy.ORCID https://orcid.org/0000-0002-3901-8983
Matteo SpositoDepartment of Advanced Robotics, Istituto Italiano di Tecnologia, XoLab, Genoa, Italy.ORCID https://orcid.org/0000-0002-7442-1399
Vasco FantiDepartment of Advanced Robotics, Istituto Italiano di Tecnologia, XoLab, Genoa, Italy.
Sergio LeggieriDepartment of Advanced Robotics, Istituto Italiano di Tecnologia, XoLab, Genoa, Italy.
Darwin G CaldwellDepartment of Advanced Robotics, Istituto Italiano di Tecnologia, XoLab, Genoa, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Assessment of occupational exoskeletons should ideally include longitudinal and multistage studies in real working scenarios to prove their effectiveness and sustainability in real in-field contexts and to help generalize the findings for specific scenarios. This work presents a comprehensive assessment methodology implemented as a multistage experimental campaign for rail industry workers using a back-support exoskeleton (StreamEXO). This work demonstrates that a sector/task-specific exoskeleton developed to address work task-specific requirements generates beneficial performance and user experience results. The experimental work in this paper involves collecting data from nine workers over multiple days of testing. During this testing, workers did not report hindrances to their work operations, with an acceptance rate of 86%. In addition, worker fatigue was reduced by 16.9% as measured through metabolic consumption, and 51% when assessed by perceived effort. This work supports the hypothesis that sector/task-specific exoskeletons when tailored to meet the needs of workers and the work tasks can produce demonstrable benefits in real industrial sectors.

Indexed as

acceptanceexperimental protocolfatigue reductionindustrial exoskeletonon-site assessmentwearable robotics

Identifiers

PMID39935597
PMCPMC11810522

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.