Evidence map›Paper›PMID 39517887›Full record

ArticleSensors (Basel, Switzerland)2024

A Cloud Infrastructure for Health Monitoring in Emergency Response Scenarios.

Alessandro Orro, Gian Angelo Geminiani, Francesco Sicurello, Marcello Modica, Francesco Pegreffi, Luca Neri, Antonio Augello, Matteo Botteghi

Abstract read
In one paragraph

Article 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 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Review
  2. Review
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

8 authors.

Alessandro OrroInstitute of Biomedical Technologies CNR, Via Fratelli Cervi, 93, 20054 Segrate, Italy.ORCID 0000-0002-2581-9579
Gian Angelo GeminianiG&G Technologies Srl, Via Tre Settembre, 99, 47891 Dogana, San Marino.
Francesco SicurelloInstitute of Biomedical Technologies CNR, Via Fratelli Cervi, 93, 20054 Segrate, Italy.ORCID 0009-0008-7377-3916
Marcello ModicaLogConsulting, Via Provinciale 175/b, Valsamoggia, 40053 Bologna, Italy.
Francesco PegreffiDepartment of Medicine and Surgery, School of Medicine and Surgery, "Kore" University of Enna, 94100 Enna, Italy.ORCID 0000-0002-6788-6040
Luca NeriDepartment of Medicine, Division of Cardiology, Johns Hopkins University, Baltimore, MD 21218, USA.ORCID 0000-0003-3971-9533
Antonio AugelloAccyourate SpA, Via Ulisse Nurzia, 1/A, 67100 L'Aquila, Italy.
Matteo BotteghiExperimental Pathology Research Group, Department of Clinical and Molecular Sciences, Università Politecnica delle Marche, 60121 Ancona, Italy.ORCID 0009-0007-9725-1277

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Wearable devices have a significant impact on society, and recent advancements in modern sensor technologies are opening up new possibilities for healthcare applications. Continuous vital sign monitoring using Internet of Things solutions can be a crucial tool for emergency management, reducing risks in rescue operations and ensuring the safety of workers. The massive amounts of data, high network traffic, and computational demands of a typical monitoring application can be challenging to manage with traditional infrastructure. Cloud computing provides a solution with its built-in resilience and elasticity capabilities. This study presents a Cloud-based monitoring architecture for remote vital sign tracking of paramedics and medical workers through the use of a mobile wearable device. The system monitors vital signs such as electrocardiograms and breathing patterns during work sessions, and it is able to manage real-time alarm events to a personnel management center. In this study, 900 paramedics and emergency workers were monitored using wearable devices over a period of 12 months. Data from these devices were collected, processed via Cloud infrastructure, and analyzed to assess the system's reliability and scalability. The results showed a significant improvement in worker safety and operational efficiency. This study demonstrates the potential of Cloud-based systems and Internet of Things devices in enhancing emergency response efforts.

Indexed as

Cloud ComputingWearable Electronic DevicesElectrocardiographyEmergency Medical ServicesEmergency RespondersHumansInternet of ThingsMonitoring, PhysiologicVital Signscloud computingdigital healthIoToccupational health monitoringreal-time emergency managementwearable device

Identifiers

PMID39517887
PMCPMC11548302

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.