Evidence map›Paper›PMID 39275383›Full record

SynthesisSensors (Basel, Switzerland)2024

Workplace Well-Being in Industry 5.0: A Worker-Centered Systematic Review.

Francesca Giada Antonaci, Elena Carlotta Olivetti, Federica Marcolin, Ivonne Angelica Castiblanco Jimenez, Benoît Eynard, Enrico Vezzetti, Sandro Moos

Abstract readSystematic Review
In one paragraph

Synthesis in Sensors (Basel, Switzerland), 2024. 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

7 authors.

Francesca Giada AntonaciDepartment of Management and Production Engineering, Politecnico di Torino, Corso Duca degli Abruzzi 24, 10129 Turin, Italy.ORCID 0009-0004-1519-5258
Elena Carlotta OlivettiDepartment of Management and Production Engineering, Politecnico di Torino, Corso Duca degli Abruzzi 24, 10129 Turin, Italy.ORCID 0000-0002-9791-5543
Federica MarcolinDepartment of Management and Production Engineering, Politecnico di Torino, Corso Duca degli Abruzzi 24, 10129 Turin, Italy.
Ivonne Angelica Castiblanco JimenezDepartment of Management and Production Engineering, Politecnico di Torino, Corso Duca degli Abruzzi 24, 10129 Turin, Italy.ORCID 0000-0001-5866-078X
Benoît EynardDepartment of Mechanical Systems Engineering, Université de Technologie de Compiègne, Centre Pierre Guillaumat, BP 60319, Rue du Docteur Schweitzer, Cedex, F-60203 Compiègne, France.ORCID 0000-0002-5393-4363
Enrico VezzettiDepartment of Management and Production Engineering, Politecnico di Torino, Corso Duca degli Abruzzi 24, 10129 Turin, Italy.
Sandro MoosDepartment of Management and Production Engineering, Politecnico di Torino, Corso Duca degli Abruzzi 24, 10129 Turin, Italy.ORCID 0000-0001-5097-7344

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The paradigm of Industry 5.0 pushes the transition from the traditional to a novel, smart, digital, and connected industry, where well-being is key to enhance productivity, optimize man-machine interaction and guarantee workers' safety. This work aims to conduct a systematic review of current methodologies for monitoring and analyzing physical and cognitive ergonomics. Three research questions are addressed: (1) which technologies are used to assess the physical and cognitive well-being of workers in the workplace, (2) how the acquired data are processed, and (3) what purpose this well-being is evaluated for. This way, individual factors within the holistic assessment of worker well-being are highlighted, and information is provided synthetically. The analysis was conducted following the PRISMA 2020 statement guidelines. From the sixty-five articles collected, the most adopted (1) technological solutions, (2) parameters, and (3) data analysis and processing were identified. Wearable inertial measurement units and RGB-D cameras are the most prevalent devices used for physical monitoring; in the cognitive ergonomics, and cardiac activity is the most adopted physiological parameter. Furthermore, insights on practical issues and future developments are provided. Future research should focus on developing multi-modal systems that combine these aspects with particular emphasis on their practical application in real industrial settings.

Indexed as

ErgonomicsWorkplaceCognitionHumansIndustryOccupational HealthWearable Electronic Devicescognitive ergonomicshuman–machine interactionhuman–robot interactionindustry 5.0physical ergonomicsworkplace well-being

Identifiers

PMID39275383
PMCPMC11398191

What OpenQuestion holds

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LicenceCC BY
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.