Evidence map›Paper›PMID 35009792›Full record

ArticleSensors (Basel, Switzerland)2021

Bionic for Training: Smart Framework Design for Multisensor Mechatronic Platform Validation.

Ruben Foresti, Rosario Statello, Nicola Delmonte, Francesco Paolo Lo Muzio, Giacomo Rozzi, Michele Miragoli, Leopoldo Sarli, Gianluigi Ferrari, Claudio Macaluso, Marcello Giuseppe Maggio and 2 more

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. SIMED-New Doc course, a matter of reflection.Acta bio-medica : Atenei Parmensis · 2023
    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

12 authors.

Ruben ForestiDepartment of Medicine and Surgery, University of Parma, 43126 Parma, Italy.ORCID 0000-0002-1060-978X
Rosario StatelloDepartment of Medicine and Surgery, University of Parma, 43126 Parma, Italy.
Nicola DelmonteDepartment of Engineering and Architecture, University of Parma, 43125 Parma, Italy.ORCID 0000-0003-2082-267X
Francesco Paolo Lo MuzioDepartment of Medicine and Surgery, University of Parma, 43126 Parma, Italy.ORCID 0000-0002-4730-2458
Giacomo RozziDepartment of Medicine and Surgery, University of Parma, 43126 Parma, Italy.ORCID 0000-0002-5085-4819
Michele MiragoliDepartment of Medicine and Surgery, University of Parma, 43126 Parma, Italy.ORCID 0000-0002-4058-4368
Leopoldo SarliDepartment of Medicine and Surgery, University of Parma, 43126 Parma, Italy.
Gianluigi FerrariDepartment of Engineering and Architecture, University of Parma, 43125 Parma, Italy.ORCID 0000-0001-6688-0934
Claudio MacalusoDepartment of Medicine and Surgery, University of Parma, 43126 Parma, Italy.
Marcello Giuseppe MaggioDepartment of Medicine and Surgery, University of Parma, 43126 Parma, Italy.
Francesco PisaniDepartment of Medicine and Surgery, University of Parma, 43126 Parma, Italy.
Cosimo CostantinoDepartment of Medicine and Surgery, University of Parma, 43126 Parma, Italy.ORCID 0000-0003-0563-5235

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Home monitoring supports the continuous improvement of the therapy by sharing data with healthcare professionals. It is required when life-threatening events can still occur after hospital discharge such as neonatal apnea. However, multiple sources of external noise could affect data quality and/or increase the misdetection rate. In this study, we developed a mechatronic platform for sensor characterizations and a framework to manage data in the context of neonatal apnea. The platform can simulate the movement of the abdomen in different plausible newborn positions by merging data acquired simultaneously from three-axis accelerometers and infrared sensors. We simulated nine apnea conditions combining three different linear displacements and body postures in the presence of self-generated external noise, showing how it is possible to reduce errors near to zero in phenomena detection. Finally, the development of a smart 8Ws-based software and a customizable mobile application were proposed to facilitate data management and interpretation, classifying the alerts to guarantee the correct information sharing without specialized skills.

Indexed as

BionicsMobile ApplicationsHumansInfant, Newborn8Wsbionicneonatal apneathree-axis accelerometerzero-failure

Identifiers

PMID35009792
PMCPMC8749724

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.