Evidence map›Paper›PMID 37655115›Full record

ArticleIEEE sensors journal2020

Wearable Vital Signs Monitoring for Patients With Asthma: A Review.

Lucy Taylor, Xiaorong Ding, David Clifton, Huiqi Lu

Open access · greenAbstract read
In one paragraph

Article in IEEE sensors journal, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
3.2field-weighted citation impact, top 7% 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

8 citing papers in PubMed, 30 citations in OpenAlex.

  1. Article
  2. Observational
  3. Article
  4. Review
  5. Review
  6. Article
  7. The 2023 wearable photoplethysmography roadmap.Physiological measurement · 2023
    Review
  8. 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

4 authors at 2 institutions in 2 countries.

Lucy TaylorSomerville College and the Department of Engineering Science, University of Oxford, OX2 6HD Oxford, U.K.ORCID 0000-0002-3455-287X
Xiaorong DingSchool of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610056, China.ORCID 0000-0002-3269-2852
David CliftonDepartment of Engineering Science, University of Oxford, OX3 7DQ Oxford, U.K., and also with the Oxford Suzhou Centre for Advanced Research, Suzhou 215000, China.
Huiqi LuSomerville College and the Department of Engineering Science, University of Oxford, OX2 6HD Oxford, U.K.ORCID 0000-0002-6140-3394
University of Oxford · GBUniversity of Electronic Science and Technology of China · CN

Funding

Department of Health NIHR302440Wellcome Trust 215010
6 · The paper itself

Abstract

Worldwide,an estimated 461 000 people die from asthma attacks each year. While there remain treatments to alleviate asthma symptoms and reduce deaths, patient deterioration needs to be identified in sufficient time. To prevent asthma deterioration, patients need to be aware of personal and environmental triggers and monitor their asthma symptoms. The aim of this article is to provide a comprehensive review of the current state-of-the-art wearable sensors and devices that use vital signs for asthma patient monitoring and management. Among all vital signs, breathing rate and airflow sound are key indicators of asthmatic patients' health that can be measured directly using wearable sensors to provide continuous and constant patient monitoring or indirectly by estimations based on proven algorithms using electrocardiogram (ECG), photoplethysmogram (PPG), and chest movements. ECG and PPG signals are widely used in smart watches and chest bands, enabling easy integration of a more extensive body sensor framework for asthmatic exacerbation prediction. Other vital signs used in asthma patient monitoring include blood oxygen saturation, temperature, blood pressure, verbal sound, and pain responses. The use of wearable vital signs enabled a broad range of wearable sensor application scenarios for asthma monitoring and management.

Indexed as

Asthmabreathing rate (BR)digital healthelectrocardiogram (ECG)mobile healthpatient monitoringphotoplethysmogram (PPG)sensorswearable technology

Identifiers

PMID37655115
PMCPMC7615004
OpenAlexW4312917049

What OpenQuestion holds

Textmetadata
LicenceTDM
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.