Evidence map›Paper›PMID 35854744›Full record

ArticleAMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science2022

VitalSeer: The development of a contactless sensing technology based on a user-centric data-driven clinical approach.

Kendall Ho, David Rivest-Henault, Nooshin Jafari, Michael Lim, Aida Hassani, Jennifer L Cordeiro, Bruno Falardeau, Linda Pecora, Catherine Pagiatakis, Faten M'hiri and 1 more

Abstract read
In one paragraph

Article in AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. 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

11 authors.

Kendall HoUniversity of British Columbia, Department of Emergency Medicine, Vancouver, British Columbia, Canada.
David Rivest-HenaultNational Research Council of Canada, Medical Devices Research Center, Boucherville, Quebec, Canada.
Nooshin JafariUniversity of British Columbia, Department of Emergency Medicine, Vancouver, British Columbia, Canada.
Michael LimUniversity of British Columbia, Department of Emergency Medicine, Vancouver, British Columbia, Canada.
Aida HassaniUniversity of British Columbia, Department of Emergency Medicine, Vancouver, British Columbia, Canada.
Jennifer L CordeiroUniversity of British Columbia, Department of Emergency Medicine, Vancouver, British Columbia, Canada.
Bruno FalardeauNational Research Council of Canada, Medical Devices Research Center, Boucherville, Quebec, Canada.
Linda PecoraNational Research Council of Canada, Medical Devices Research Center, Boucherville, Quebec, Canada.
Catherine PagiatakisNational Research Council of Canada, Medical Devices Research Center, Boucherville, Quebec, Canada.
Faten M'hiriNational Research Council of Canada, Medical Devices Research Center, Boucherville, Quebec, Canada.
Di JiangNational Research Council of Canada, Medical Devices Research Center, Boucherville, Quebec, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The COVID-19 pandemic presented challenges to the healthcare system while catalyzing the adoption of virtual care. The need for remote assessment and real-time monitoring of physiological vital signs has driven towards a need for virtual care solutions. This paper presents the outcome of a multidisciplinary collaboration to ensure clinical usability of a remote contactless sensing technology, VitalSeer, and to help close gaps between emerging technologies and clinical practice. The paper describes the user-centric data-driven clinical approach to address the needs as identified by clinical experts through the iterative and agile development cycle. It highlights findings from preliminary studies to validate proof-of-concept VitalSeer's adoptability, accessibility and usability. The studies on volunteers demonstrated the accuracy of VitalSeer's heart rate model at a low MAE of 0.74 (bpm) and a RMSE of 1.2 bpm, below the threshold of clinical grade contact-based sensors. The paper concludes with a discussion on the technology implications in emergency medicine and community care.

Identifiers

PMID35854744
PMCPMC9285145

What OpenQuestion holds

Textmetadata
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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.