Evidence map›Paper›PMID 40336969›Full record

ArticleWearable technologies2025

SenseRisc: An instrumented smart shirt for risk prevention in the workplace.

Christian Tamantini, Fabrizio Marra, Joshua Di Tocco, Stefano Di Modica, Antonio Lanata, Francesca Cordella, Maurizio Ferrarin, Francesco Rizzo, Mara Stefanelli, Maddalena Papacchini and 6 more

Abstract read
PubMed Full text at PMC Publisher
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 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

16 authors.

Christian TamantiniInstitute of Cognitive Sciences and Technologies, National Research Council of Italy, Rome, Italy.ORCID https://orcid.org/0000-0001-6238-2241
Fabrizio MarraDepartment of Astronautics, Electrical and Energy Engineering (DIAEE), University of Roma La Sapienza, Rome, Italy.
Joshua Di ToccoUnit of Measurements and Biomedical Instrumentation, Departmental Faculty of Engineering, Università Campus Bio-Medico di Roma, Rome, Italy.
Stefano Di ModicaIntecs s.p.a, Rome, Italy.
Antonio LanataDepartment of Information Engineering, University of Florence, Florence, Italy.
Francesca CordellaUnit of Advanced Robotics and Human-Centred Technologies, Departmental Faculty of Engineering, Università Campus Bio-Medico di Roma, Rome, Italy.
Maurizio FerrarinIRCCS Fondazione Don Carlo Gnocchi Onlus, Milan, Italy.ORCID https://orcid.org/0000-0002-7797-2399
Francesco RizzoIRCCS Fondazione Don Carlo Gnocchi Onlus, Milan, Italy.
Mara StefanelliDepartment of Technological Innovations and Safety of Plants, Products and Anthropic Settlements (DITSIPIA), National Institute for Insurance against Accidents at Work (INAIL), Rome, Italy.
Maddalena PapacchiniDepartment of Technological Innovations and Safety of Plants, Products and Anthropic Settlements (DITSIPIA), National Institute for Insurance against Accidents at Work (INAIL), Rome, Italy.
Corrado Delle SiteDepartment of Technological Innovations and Safety of Plants, Products and Anthropic Settlements (DITSIPIA), National Institute for Insurance against Accidents at Work (INAIL), Rome, Italy.
Alessio TamburranoDepartment of Astronautics, Electrical and Energy Engineering (DIAEE), University of Roma La Sapienza, Rome, Italy.
Carlo MassaroniUnit of Measurements and Biomedical Instrumentation, Departmental Faculty of Engineering, Università Campus Bio-Medico di Roma, Rome, Italy.
Emiliano SchenaUnit of Measurements and Biomedical Instrumentation, Departmental Faculty of Engineering, Università Campus Bio-Medico di Roma, Rome, Italy.
Loredana ZolloUnit of Advanced Robotics and Human-Centred Technologies, Departmental Faculty of Engineering, Università Campus Bio-Medico di Roma, Rome, Italy.
Maria Sabrina SartoDepartment of Astronautics, Electrical and Energy Engineering (DIAEE), University of Roma La Sapienza, Rome, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The integration of wearable smart garments with multiple sensors has gained momentum, enabling real-time monitoring of users' vital parameters across various domains. This study presents the development and validation of an instrumented smart shirt for risk prevention in workplaces designed to enhance worker safety and well-being in occupational settings. The proposed smart shirt is equipped with sensors for collecting electrocardiogram, respiratory waveform, and acceleration data, with signal conditioning electronics and Bluetooth transmission to the mobile application. The mobile application sends the data to the cloud platform for subsequent Preventive Risk Index (PRI) extraction. The proposed SenseRisc system was validated with eight healthy participants during the execution of different physically exerting activities to assess the capability of the system to capture physiological parameters and estimate the PRI of the worker, and user subjective perception of the instrumented intelligent shirt.

Indexed as

cloud computinggraphene sensorsuser state estimationwearable system

Identifiers

PMID40336969
PMCPMC12056430

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.