Evidence map›Paper›PMID 29572752›Full record

ArticleJournal of medical systems2018

Development of a Smart Mobile Data Module for Fetal Monitoring in E-Healthcare.

Agathe Houzé de l'Aulnoit, Samuel Boudet, Michaël Génin, Pierre-François Gautier, Jessica Schiro, Denis Houzé de l'Aulnoit, Régis Beuscart

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In one paragraph

Article in Journal of medical systems, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
6.4field-weighted citation impact, top 4% 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

9 citing papers in PubMed, 35 citations in OpenAlex.

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  7. Trends, Technologies, and Key Challenges in Smart and Connected Healthcare.IEEE access : practical innovations, open solutions · 2021
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  9. Observational
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

7 authors at 3 institutions in 1 country.

Agathe Houzé de l'AulnoitUniv Nord de France; CHU Lille, UDSL EA2694, F-59000, Lille, France. ahouzedelaulnoit@yahoo.fr.ORCID http://orcid.org/0000-0003-4770-9271
Samuel BoudetBiomedical Signal Processing Unit (UTSB), Lille Catholic University, F-59800, Lille, France.
Michaël GéninUniv Nord de France; CHU Lille, UDSL EA2694, F-59000, Lille, France.
Pierre-François GautierUniv Nord de France; INSERM, CHU Lille, CIC 1403, F-59000, Lille, France.
Jessica SchiroUniv Nord de France; INSERM, CHU Lille, CIC 1403, F-59000, Lille, France.
Denis Houzé de l'AulnoitObstetrics Department, Lille Catholic Hospital, Lille Catholic University, F-59020, Lille, France.
Régis BeuscartUniv Nord de France; CHU Lille, UDSL EA2694, F-59000, Lille, France.
Université Catholique de Lille · FRInserm · FRUniversité de Lille · FR

Funding

Aviesan N°2016-017
6 · The paper itself

Abstract

The fetal heart rate (FHR) is a marker of fetal well-being in utero (when monitoring maternal and/or fetal pathologies) and during labor. Here, we developed a smart mobile data module for the remote acquisition and transmission (via a Wi-Fi or 4G connection) of FHR recordings, together with a web-based viewer for displaying the FHR datasets on a computer, smartphone or tablet. In order to define the features required by users, we modelled the fetal monitoring procedure (in home and hospital settings) via semi-structured interviews with midwives and obstetricians. Using this information, we developed a mobile data transfer module based on a Raspberry Pi. When connected to a standalone fetal monitor, the module acquires the FHR signal and sends it (via a Wi-Fi or a 3G/4G mobile internet connection) to a secure server within our hospital information system. The archived, digitized signal data are linked to the patient's electronic medical records. An HTML5/JavaScript web viewer converts the digitized FHR data into easily readable and interpretable graphs for viewing on a computer (running Windows, Linux or MacOS) or a mobile device (running Android, iOS or Windows Phone OS). The data can be viewed in real time or offline. The application includes tools required for correct interpretation of the data (signal loss calculation, scale adjustment, and precise measurements of the signal's characteristics). We performed a proof-of-concept case study of the transmission, reception and visualization of FHR data for a pregnant woman at 30 weeks of amenorrhea. She was hospitalized in the pregnancy assessment unit and FHR data were acquired three times a day with a Philips Avalon® FM30 fetal monitor. The prototype (Raspberry Pi) was connected to the fetal monitor's RS232 port. The emission and reception of prerecorded signals were tested and the web server correctly received the signals, and the FHR recording was visualized in real time on a computer, a tablet and smartphones (running Android and iOS) via the web viewer. This process did not perturb the hospital's computer network. There was no data delay or loss during a 60-min test. The web viewer was tested successfully in the various usage situations. The system was as user-friendly as expected, and enabled rapid, secure archiving. We have developed a system for the acquisition, transmission, recording and visualization of RCF data. Healthcare professionals can view the FHR data remotely on their computer, tablet or smartphone. Integration of FHR data into a hospital information system enables optimal, secure, long-term data archiving.

Indexed as

Heart Rate, FetalMobile ApplicationsSmartphoneFetal MonitoringHumansImage Processing, Computer-AssistedTelemetryTime FactorsWireless TechnologyArchivingFetal heart rate recordingFetal monitoringSmart device

Identifiers

PMID29572752
OpenAlexW2793379392

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.