Evidence map›Paper›PMID 34199446›Full record

ReviewSensors (Basel, Switzerland)2021

Wearables for Industrial Work Safety: A Survey.

Ekaterina Svertoka, Salwa Saafi, Alexandru Rusu-Casandra, Radim Burget, Ion Marghescu, Jiri Hosek, Aleksandr Ometov

Abstract readReview
In one paragraph

Review in Sensors (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
28citing papers in PubMed, 2 pooled it
–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

28 citing papers in PubMed, 2 syntheses or guidelines pooled it.

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  20. [Research progress on minimally invasive and non-invasive blood glucose detection methods].Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi · 2023
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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.

Ekaterina SvertokaDepartment of Telecommunications, Faculty of Electronics, Telecommunications and Information Technology, University Politehnica of Bucharest, 061071 Bucharest, Romania.ORCID 0000-0001-6384-5113
Salwa SaafiDepartment of Telecommunications, Faculty of Electrical Engineering and Communication, Brno University of Technology, Technicka 12, 616 00 Brno, Czech Republic.ORCID 0000-0002-2786-9377
Alexandru Rusu-CasandraDepartment of Telecommunications, Faculty of Electronics, Telecommunications and Information Technology, University Politehnica of Bucharest, 061071 Bucharest, Romania.ORCID 0000-0003-3242-3561
Radim BurgetDepartment of Telecommunications, Faculty of Electrical Engineering and Communication, Brno University of Technology, Technicka 12, 616 00 Brno, Czech Republic.ORCID 0000-0003-1849-5390
Ion MarghescuDepartment of Telecommunications, Faculty of Electronics, Telecommunications and Information Technology, University Politehnica of Bucharest, 061071 Bucharest, Romania.ORCID 0000-0003-3111-8645
Jiri HosekDepartment of Telecommunications, Faculty of Electrical Engineering and Communication, Brno University of Technology, Technicka 12, 616 00 Brno, Czech Republic.ORCID 0000-0002-8382-9185
Aleksandr OmetovUnit of Electrical Engineering, Faculty of Information Technology and Communication Sciences, Tampere University, 33720 Tampere, Finland.ORCID 0000-0003-3412-1639

Funding

This research was funded by European Union's Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie 813278
6 · The paper itself

Abstract

Today, ensuring work safety is considered to be one of the top priorities for various industries. Workplace injuries, illnesses, and deaths often entail substantial production and financial losses, governmental checks, series of dismissals, and loss of reputation. Wearable devices are one of the technologies that flourished with the fourth industrial revolution or Industry 4.0, allowing employers to monitor and maintain safety at workplaces. The purpose of this article is to systematize knowledge in the field of industrial wearables' safety to assess the relevance of their use in enterprises as the technology maintaining occupational safety, to correlate the benefits and costs of their implementation, and, by identifying research gaps, to outline promising directions for future work in this area. We categorize industrial wearable functions into four classes (monitoring, supporting, training, and tracking) and provide a classification of the metrics collected by wearables to better understand the potential role of wearable technology in preserving workplace safety. Furthermore, we discuss key communication technologies and localization techniques utilized in wearable-based work safety solutions. Finally, we analyze the main challenges that need to be addressed to further enable and support the use of wearable devices for industrial work safety.

Indexed as

Occupational HealthWearable Electronic DevicesMonitoring, PhysiologicSurveys and QuestionnairesWorkplacecommunicationsdata collectionIIoTlocalizationoccupational safetysmart deviceswearables

Identifiers

PMID34199446
PMCPMC8199604

What OpenQuestion holds

Textmetadata
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.