Evidence map›Paper›PMID 36569387›Full record

ArticleBiomedical signal processing and control2021

IoT garment for remote elderly care network.

Francisco Luna-Perejón, Luis Muñoz-Saavedra, Jose M Castellano-Domínguez, Manuel Domínguez-Morales

Open access · greenAbstract read
In one paragraph

Article in Biomedical signal processing and control, 2021. 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
1.9field-weighted citation impact, top 12% 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

2 citing papers in PubMed, 22 citations in OpenAlex.

  1. Design of Innovative Clothing for Pressure Injury Prevention: End-User Evaluation in a Mixed-Methods Study.International journal of environmental research and public health · 2023
    Article
  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

4 authors at 1 institution in 1 country.

Francisco Luna-PerejónArchitecture and Computer Technology Department, ETSII-EPS, University of Seville, Seville, Spain.
Luis Muñoz-SaavedraArchitecture and Computer Technology Department, ETSII-EPS, University of Seville, Seville, Spain.
Jose M Castellano-DomínguezArchitecture and Computer Technology Department, ETSII-EPS, University of Seville, Seville, Spain.
Manuel Domínguez-MoralesArchitecture and Computer Technology Department, ETSII-EPS, University of Seville, Seville, Spain.
Universidad de Sevilla · ES

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The elderly is a continuous growth sector thanks to the life expectancy increase in Western society. This sector is especially at risk from the appearance of respiratory diseases and, therefore, is the most affected sector in the COVID-19 epidemic. Many of these elderly require continuous care in residences or by specialized caregivers, but these personal contacts put this sector at risk. In this work, an IoT system for elderly remote monitoring is studied, designed, developed and tested. This system is composed by a smart garment that records information from various physiological sensors in order to detect falls, sudden changes in body temperature, heart problems and heat stroke; This information is sent to a cloud server through a gateway located in the patient's residence, allowing to real-time monitor remotely patient's activity using a customized App, as well as receiving alerts in dangerous situations. This system has been tested with professional caregivers, obtaining usability and functionality surveys; and, in addition, a detailed power-consumption study has been carried out. The results, compared with other similar systems, demonstrate that the proposed one is useful, usable, works in real time and has a decent power consumption that allows the patient to carry it during all day without charging the battery.

Indexed as

AccelerometerCOVID-19ElderlyElectrocardiographEmbedded systemFallGalvanic skin responseIoTSkin temperature

Identifiers

PMID36569387
PMCPMC9760329
OpenAlexW3175942355

What OpenQuestion holds

Textmetadata
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.