Evidence map›Paper›PMID 34208252›Full record

ArticleInternational journal of environmental research and public health2021

MoSIoT: Modeling and Simulating IoT Healthcare-Monitoring Systems for People with Disabilities.

Santiago Meliá, Shahabadin Nasabeh, Sergio Luján-Mora, Cristina Cachero

Open access · goldAbstract read
In one paragraph

Article in International journal of environmental research and public health, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
2.0field-weighted citation impact, top 11% of its field
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

4 citing papers in PubMed, 34 citations in OpenAlex.

  1. Review
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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

4 authors at 1 institution in 1 country.

Santiago MeliáDepartamento de Lenguajes y Sistemas Informáticos, Universidad de Alicante, Carretera de San Vicente s/n, 03690 San Vicente del Raspeig, Alicante, Spain.
Shahabadin NasabehDepartamento de Lenguajes y Sistemas Informáticos, Universidad de Alicante, Carretera de San Vicente s/n, 03690 San Vicente del Raspeig, Alicante, Spain.
Sergio Luján-MoraDepartamento de Lenguajes y Sistemas Informáticos, Universidad de Alicante, Carretera de San Vicente s/n, 03690 San Vicente del Raspeig, Alicante, Spain.ORCID 0000-0001-5000-864X
Cristina CacheroDepartamento de Lenguajes y Sistemas Informáticos, Universidad de Alicante, Carretera de San Vicente s/n, 03690 San Vicente del Raspeig, Alicante, Spain.
University of Alicante · ES

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The need to remotely monitor people with disabilities has increased due to growth in their number in recent years. The democratization of Internet of Things (IoT) devices facilitates the implementation of healthcare-monitoring systems (HMSs) that are capable of supporting disabilities and diseases. However, to achieve their full potential, these devices must efficiently address the customization demanded by different IoT HMS scenarios. This work introduces a new approach, called Modeling Scenarios of Internet of Things (MoSIoT), which allows healthcare experts to model and simulate IoT HMS scenarios defined for different disabilities and diseases. MoSIoT comprises a set of models based on the model-driven engineering (MDE) paradigm, which first allows simulation of a complete IoT HMS scenario, followed by generation of a final IoT system. In the current study, we used a real scenario defined by a recognized medical publication for a patient with Alzheimer's disease to validate this proposal. Furthermore, we present an implementation based on an enterprise cloud architecture that provides the simulation data to a commercial IoT hub, such as Azure IoT Central.

Indexed as

Internet of ThingsPersons with DisabilitiesDelivery of Health CareElectrocardiographyHumansMonitoring, PhysiologicAlzheimer’sAzure IoT CentraldisabilitiesFHIRhealthcare-monitoring systemInternet of Thingsmachine-learning MDEmodel-driven engineeringsimulatortrigger–action programming

Identifiers

PMID34208252
PMCPMC8296168
OpenAlexW3172035597

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.