Evidence map›Paper›PMID 33806399›Full record

ArticleSensors (Basel, Switzerland)2021

Evaluation of Functionality of Warning System in Smart Protective Clothing for Firefighters.

Anna Dąbrowska, Grażyna Bartkowiak, Rafał Kotas

Abstract read
In one paragraph

Article 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 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

3 authors.

Anna DąbrowskaDepartment of Personal Protective Equipment, Central Institute for Labour Protection-National Research Institute, 90-133 Lodz, Poland.ORCID 0000-0003-4295-3005
Grażyna BartkowiakDepartment of Personal Protective Equipment, Central Institute for Labour Protection-National Research Institute, 90-133 Lodz, Poland.
Rafał KotasDepartment of Microelectronics and Computer Science, Lodz University of Technology, 90-924 Lodz, Poland.ORCID 0000-0003-0776-9173

Funding

Ministerstwo Nauki i Szkolnictwa Wyższego III.N.16Narodowe Centrum Badań i Rozwoju III.N.16
6 · The paper itself

Abstract

Recent achievements in the field of miniaturization of electronics have led to a significant interest in its application into the protective clothing for firefighters in order to improve their safety and health. However, up to now there are not any requirements and standardized test methods enabling confirmation of safety of use and functionality of these systems in work environment. In the paper, an importance of evaluation of such smart wearable system in predicted utility conditions is highlighted. Three variants of the specially developed personal warning systems (PWSs) for integration with either health status or environmental sensors to be used in smart protective clothing for firefighters are presented, i.e., with LCD display, LED diodes and vibrating element. For the purpose of evaluation a new testing methodology was developed. The PWSs were evaluated on a basis of perception of warning signals by firefighters in simulated utility conditions including temperature, light, noise, fog and performed activities. In the case of marching, even 75% of signals generated by PWS with LCD display were not received. Physical activity did not influence on functionality of PWS with vibrating element. For the PWS with LED diodes, the signal was received statistically significantly quicker than in the case of other PWS and the mean value of voice response time was below 3 s.

Indexed as

FirefightersHumansProtective Clothingfirefighterssmart clothingsmart PPEwarning systemswearables

Identifiers

PMID33806399
PMCPMC7962023

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.