Evidence map›Paper›PMID 34476669›Full record

ArticleJournal of clinical monitoring and computing2022

Clinical evaluation of a wearable sensor for mobile monitoring of respiratory rate on hospital wards.

Kristiina Järvelä, Panu Takala, Frederic Michard, Leena Vikatmaa

Open access · hybridAbstract read
In one paragraph

Article in Journal of clinical monitoring and computing, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
2.7field-weighted citation impact, top 9% 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

9 citing papers in PubMed, 17 citations in OpenAlex.

  1. Article
  2. Review
  3. Continuous vital sign monitoring with BiobeatJournal of clinical monitoring and computing · 2025
    Observational
  4. Review
  5. Review
  6. Observational
  7. Article
  8. Article
  9. One small wearable, one giant leap for patient safety?Journal of clinical monitoring and computing · 2022
    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 1 country.

Kristiina JärveläResearch & Development, GE Healthcare, Helsinki, Finland.
Panu TakalaResearch & Development, GE Healthcare, Helsinki, Finland.
Frederic MichardMiCo, Denens, Switzerland. frederic.michard@bluewin.ch.ORCID 0000-0001-9749-3515
Leena VikatmaaDepartment of Anesthesia, Intensive Care and Pain Medicine, Helsinki University Hospital and University of Helsinki, Helsinki, Finland.
General Electric (Finland) · FIUniversity of Helsinki · FI

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A wireless and wearable system was recently developed for mobile monitoring of respiratory rate (RR). The present study was designed to compare RR mobile measurements with reference capnographic measurements on a medical-surgical ward. The wearable sensor measures impedance variations of the chest from two thoracic and one abdominal electrode. Simultaneous measurements of RR from the wearable sensor and from the capnographic sensor (1 measure/minute) were compared in 36 ward patients. Patients were monitored for a period of 182 ± 56 min (range 68-331). Artifact-free RR measurements were available 81% of the monitoring time for capnography and 92% for the wearable monitoring system (p < 0.001). A total of 4836 pairs of simultaneous measurements were available for analysis. The average reference RR was 19 ± 5 breaths/min (range 6-36). The average difference between the wearable and capnography RR measurements was - 0.6 ± 2.5 breaths/min. Error grid analysis showed that the proportions of RR measurements done with the wearable system were 89.7% in zone A (no risk), 9.6% in zone B (low risk) and < 1% in zones C, D and E (moderate, significant and dangerous risk). The wearable method detected RR values > 20 (tachypnea) with a sensitivity of 81% and a specificity of 93%. In ward patients, the wearable sensor enabled accurate and precise measurements of RR within a relatively broad range (6-36 b/min) and the detection of tachypnea with high sensitivity and specificity.

Indexed as

Respiratory RateWearable Electronic DevicesHospitalsHumansMonitoring, PhysiologicTachypneaRemote monitoringRespiratory frequencyThoracic impedanceWard monitoringWearable sensorWireless monitoring

Identifiers

PMID34476669
PMCPMC8894146
OpenAlexW3197695918

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.