Evidence map›Paper›PMID 34659594›Full record

ArticleProcedia computer science2021

Non-invasive devices for respiratory sound monitoring.

Ángela Troncoso, Juan A Ortega, Ralf Seepold, Natividad Martínez Madrid

Abstract read
In one paragraph

Article in Procedia computer science, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed, 1 pooled it
–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

5 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Review
  3. Review
  4. Review
  5. 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.

Ángela TroncosoUniversity of Seville, Avda. Reina Mercedes s/n, 41012 Seville, Spain.
Juan A OrtegaUniversity of Seville, Avda. Reina Mercedes s/n, 41012 Seville, Spain.
Ralf SeepoldHTWG Konstanz, Alfred-Wachtel-Str. 8, 78462 Konstanz, Germany.
Natividad Martínez MadridReutlingen University, Alteburgstr. 150, 72762 Reutlingen, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Respiratory diseases are leading causes of death and disability in the world. The recent COVID-19 pandemic is also affecting the respiratory system. Detecting and diagnosing respiratory diseases requires both medical professionals and the clinical environment. Most of the techniques used up to date were also invasive or expensive. Some research groups are developing hardware devices and techniques to make possible a non-invasive or even remote respiratory sound acquisition. These sounds are then processed and analysed for clinical, scientific, or educational purposes. We present the literature review of non-invasive sound acquisition devices and techniques. The results are about a huge number of digital tools, like microphones, wearables, or Internet of Thing devices, that can be used in this scope. Some interesting applications have been found. Some devices make easier the sound acquisition in a clinic environment, but others make possible daily monitoring outside that ambient. We aim to use some of these devices and include the non-invasive recorded respiratory sounds in a Digital Twin system for personalized health.

Indexed as

acquisitionInternet of Thingsnon-invasiverespiratory soundssmartphonestethoscopewearable

Identifiers

PMID34659594
PMCPMC8504165

What OpenQuestion holds

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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.