Evidence map›Paper›PMID 32449051›Full record

ArticleIntensive care medicine experimental2020

Method of respiratory rate measurement using a unique wearable platform and an adaptive optical-based approach.

Gurpreet Singh, Augustine Tee, Thanawin Trakoolwilaiwan, Aza Taha, Malini Olivo

Open access · goldAbstract read
In one paragraph

Article in Intensive care medicine experimental, 2020. 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
1.4field-weighted citation impact, top 21% 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, 29 citations in OpenAlex.

  1. Article
  2. Review
  3. Article
  4. Article
  5. Article
  6. Review
  7. Article
  8. Review
  9. End-to-end design of wearable sensors.Nature reviews. Materials · 2022
    Review
  10. Review
  11. Observational
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 at 2 institutions in 1 country.

Gurpreet SinghLaboratory of Bio-Optical Imaging, Singapore Bioimaging Consortium, Agency for Science Technology and Research, Singapore, Singapore. gurpreet_singh@sbic.a-star.edu.sg.ORCID http://orcid.org/0000-0001-8282-2048
Augustine TeeDepartment of Respiratory and Critical Care Medicine, Changi General Hospital, Singapore, Singapore.
Thanawin TrakoolwilaiwanLaboratory of Bio-Optical Imaging, Singapore Bioimaging Consortium, Agency for Science Technology and Research, Singapore, Singapore.
Aza TahaDepartment of Respiratory and Critical Care Medicine, Changi General Hospital, Singapore, Singapore.
Malini OlivoLaboratory of Bio-Optical Imaging, Singapore Bioimaging Consortium, Agency for Science Technology and Research, Singapore, Singapore.
Agency for Science, Technology and Research · SGChangi General Hospital · SG

Funding

A*STAR ETPL/17-GAP014-R20H
6 · The paper itself

Abstract

backgroundAn efficient and accurate method of respiratory rate measurement is still missing in hospital general wards and triage. The goal of this study is to propose a method of respiratory rate measurement that has a potential to be used in general wards, triage, and different hospital settings with comparable performance. We propose a method of respiratory rate measurement that combines a unique wearable platform with an adaptive and optical approach. The optical approach is based on a direct-contact optical diffuse reflectance phenomenon. An adaptive algorithm is developed that computes the first respiratory rate and uses it to select a band. The band then chooses a set of unique optimized parameters in the algorithm to calculate and improve the respiratory rate. We developed a study to compare the proposed method against reference manual counts from 82 patients diagnosed with respiratory diseases.

resultsWe found good agreement between the proposed method of respiratory rate measurement and reference manual counts. The performance of the proposed method highlighted deviations with a 95% confidence interval (C.I.) of - 3.34 and 3.67 breaths per minute (bpm) and a mean bias and standard deviation (STD) of 0.05 bpm and 2.56 bpm, respectively.

conclusionsThe performance of the proposed method of respiratory rate measurement is comparable with current manual counting and other respiratory rate devices reported. The method has additional advantages that include ease-of-use, quick setup time, and being mobile for wider clinical use. The proposed method has the potential as a tool to measure respiratory rates in a number of use cases.

Indexed as

AutomatedBreathing patternGeneral wardsManual countsRespiratory rateTechnology

Identifiers

PMID32449051
PMCPMC7246231
OpenAlexW3026792264

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.