Evidence map›Paper›PMID 35582518›Full record

ArticleIEEE embedded systems letters2022

A Remote Control System for Emergency Ventilators During SARS-CoV-2.

Michael Barrow, Francesco Restuccia, Mustafa Gobulukoglu, Enrico Rossi, Ryan Kastner

Abstract read
In one paragraph

Article in IEEE embedded systems letters, 2022. 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. 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

5 authors.

Michael BarrowDepartment of Computer Science and EngineeringUniversity of California at San Diego La Jolla CA 92093 USA.ORCID https://orcid.org/0000-0002-9000-0543
Francesco RestucciaScuola Superiore Sant'Anna 56127 Pisa Italy.ORCID https://orcid.org/0000-0001-6955-1888
Mustafa GobulukogluDepartment of Computer Science and EngineeringUniversity of California at San Diego La Jolla CA 92093 USA.ORCID https://orcid.org/0000-0002-5825-5300
Enrico RossiELIOS-Tech Srl 56019 Vecchiano Italy.ORCID https://orcid.org/0000-0001-6990-8381
Ryan KastnerDepartment of Computer Science and EngineeringUniversity of California at San Diego La Jolla CA 92093 USA.ORCID https://orcid.org/0000-0001-9062-5570

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

As COVID-19 began to grip healthcare systems worldwide, worst-case models predicted huge demands for ventilators. The global community sprang to action, producing a large number of emergency "makeshift" ventilator designs. This brought about another problem: a gap between the quantity of new mechanical ventilators and the number of skilled physicians to operate them. New physicians could not complete training at the pace of ventilator production, which threatened to leave patients sitting untreated, next to unusable ventilators. To address this challenge, we developed a universal remote control system for makeshift ventilators that uses low-cost hardware add-on modules to connect to different ventilators, and a three-tier control architecture to interface the ventilators with telemedicine software. We demonstrate system integration with two representative ventilator designs, adding a remote control option that allows caregivers to quickly and easily monitor and control these ventilators remotely.

Indexed as

Open source hardwarepublic healthcareresource managementtelemedicine

Identifiers

PMID35582518
PMCPMC8956371

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.