Evidence map›Paper›PMID 31357390›Full record

ArticleSensors (Basel, Switzerland)2019

IoT Based Heart Activity Monitoring Using Inductive Sensors.

Adrian Brezulianu, Oana Geman, Marius Dan Zbancioc, Marius Hagan, Cristian Aghion, D Jude Hemanth, Le Hoang Son

Open access · goldAbstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
6.1field-weighted citation impact, top 3% 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

11 citing papers in PubMed, 64 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
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 4 institutions in 3 countries.

Adrian BrezulianuFaculty of Electronics, Telecommunications and Information Technology, "Gheorghe Asachi" Technical University from Iaşi, Iaşi 700050, Romania.
Oana GemanDepartment of Health and Human Development, Stefan cel Mare University, Suceava 720229, Romania.ORCID 0000-0002-8347-8733
Marius Dan ZbanciocFaculty of Electronics, Telecommunications and Information Technology, "Gheorghe Asachi" Technical University from Iaşi, Iaşi 700050, Romania.
Marius HaganFaculty of Electronics, Telecommunications and Information Technology, "Gheorghe Asachi" Technical University from Iaşi, Iaşi 700050, Romania.
Cristian AghionFaculty of Electronics, Telecommunications and Information Technology, "Gheorghe Asachi" Technical University from Iaşi, Iaşi 700050, Romania.
D Jude HemanthDepartment of ECE, Karunya Institute of Technology and Sciences, Coimbatore, Tamilnadu 641114, India.
Le Hoang SonDivision of Data Science, Ton Duc Thang University, Ho Chi Minh City 700000, Vietnam. lehoangson@tdtu.edu.vn.
Gheorghe Asachi Technical University of Iași · ROKarunya University · INŞtefan cel Mare University of Suceava · ROTon Duc Thang University · VN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This paper presents a system dedicated to monitoring the heart activity parameters using Electrocardiography (ECG) mobile devices and a Wearable Heart Monitoring Inductive Sensor (WHMIS) that represents a new method and device, developed by us as an experimental model, used to assess the mechanical activity of the hearth using inductive sensors that are inserted in the fabric of the clothes. Only one inductive sensor is incorporated in the clothes in front of the apex area and it is able to assess the cardiorespiratory activity while in the prior of the art are presented methods that predict sensors arrays which are distributed in more places of the body. The parameters that are assessed are heart data-rate and respiration. The results are considered preliminary in order to prove the feasibility of this method. The main goal of the study is to extract the respiration and the data-rate parameters from the same output signal generated by the inductance-to-number convertor using a proper algorithm. The conceived device is meant to be part of the "wear and forget" equipment dedicated to monitoring the vital signs continuously.

Indexed as

Biosensing TechniquesMonitoring, PhysiologicAlgorithmsElectrocardiographyHeartHeart RateHumansRespirationTextilesWearable Electronic Devicesheart rate sensinginductive sensorinductive to number convertorIoTrespiration sensingtextile-based sensorUH

Identifiers

PMID31357390
PMCPMC6695716
OpenAlexW2964255387

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.