Evidence map›Paper›PMID 25230306›Full record

ArticleSensors (Basel, Switzerland)2014

Smart multi-level tool for remote patient monitoring based on a wireless sensor network and mobile augmented reality.

Fernando Cornelio Jiménez González, Osslan Osiris Vergara Villegas, Dulce Esperanza Torres Ramírez, Vianey Guadalupe Cruz Sánchez, Humberto Ochoa Domínguez

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

13 citing papers in PubMed.

  1. Trial
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  4. Remote Arrhythmia Detection for Eldercare in Malaysia.Sensors (Basel, Switzerland) · 2021
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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

5 authors.

Fernando Cornelio Jiménez GonzálezDepartamento de Ingeniería, Universidad Tecnológica de Ciudad Juárez, Av. Universidad Tecnológica 3051, Ciudad Juárez, Chihuahua, Mexico. fernando_jimenez@utcj.edu.mx.
Osslan Osiris Vergara VillegasInstituto de Ingeniería y Tecnología, Universidad Autónoma de Ciudad Juárez, Av. del Charro, 450 norte, Ciudad Juárez, Chihuahua, Mexico. overgara@uacj.mx.
Dulce Esperanza Torres RamírezDepartamento de Ingeniería, Universidad Tecnológica de Ciudad Juárez, Av. Universidad Tecnológica 3051, Ciudad Juárez, Chihuahua, Mexico. dulce_torres@utcj.edu.mx.
Vianey Guadalupe Cruz SánchezInstituto de Ingeniería y Tecnología, Universidad Autónoma de Ciudad Juárez, Av. del Charro, 450 norte, Ciudad Juárez, Chihuahua, Mexico. vianey.cruz@uacj.mx.
Humberto Ochoa DomínguezInstituto de Ingeniería y Tecnología, Universidad Autónoma de Ciudad Juárez, Av. del Charro, 450 norte, Ciudad Juárez, Chihuahua, Mexico. hochoa@uacj.mx.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Technological innovations in the field of disease prevention and maintenance of patient health have enabled the evolution of fields such as monitoring systems. One of the main advances is the development of real-time monitors that use intelligent and wireless communication technology. In this paper, a system is presented for the remote monitoring of the body temperature and heart rate of a patient by means of a wireless sensor network (WSN) and mobile augmented reality (MAR). The combination of a WSN and MAR provides a novel alternative to remotely measure body temperature and heart rate in real time during patient care. The system is composed of (1) hardware such as Arduino microcontrollers (in the patient nodes), personal computers (for the nurse server), smartphones (for the mobile nurse monitor and the virtual patient file) and sensors (to measure body temperature and heart rate), (2) a network layer using WiFly technology, and (3) software such as LabView, Android SDK, and DroidAR. The results obtained from tests show that the system can perform effectively within a range of 20 m and requires ten minutes to stabilize the temperature sensor to detect hyperthermia, hypothermia or normal body temperature conditions. Additionally, the heart rate sensor can detect conditions of tachycardia and bradycardia.

Indexed as

Body TemperatureComputer Communication NetworksElectrocardiography, AmbulatoryEquipment DesignEquipment Failure AnalysisHeart RateHumansSoftwareTelemedicineThermographyUser-Computer InterfaceWireless Technology

Identifiers

PMID25230306
PMCPMC4208221

What OpenQuestion holds

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LicenceCC BY
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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.