Evidence map›Paper›PMID 37010708›Full record

ArticleJournal of clinical monitoring and computing2023

Robust Non-Contact Monitoring of Respiratory Rate using a Depth Camera.

Paul S Addison, André Antunes, Dean Montgomery, Philip Smit, Ulf R Borg

Abstract read
In one paragraph

Article in Journal of clinical monitoring and computing, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Noncontact respiratory monitoring during sleep: comparison of the touchless flow signal with respiratory inductance plethysmography flow (RIPJournal of clinical sleep medicine : JCSM : official publication of the American Academy of Sleep Medicine · 2025
    Article
  6. Non-Contact Monitoring of Inhalation-Exhalation (I:E) Ratio in Non-Ventilated Subjects.IEEE journal of translational engineering in health and medicine · 2024
    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.

Paul S AddisonMedtronic Patient Monitoring, Technopole Centre, Edinburgh, UK. paul.addison@medtronic.com.
André AntunesMedtronic Patient Monitoring, Technopole Centre, Edinburgh, UK.
Dean MontgomeryMedtronic Patient Monitoring, Technopole Centre, Edinburgh, UK.
Philip SmitMedtronic Patient Monitoring, Technopole Centre, Edinburgh, UK.
Ulf R BorgMedtronic Patient Monitoring, Boulder, CO, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeRespiratory rate (RR) is one of the most common vital signs with numerous clinical uses. It is an important indicator of acute illness and a significant change in RR is often an early indication of a potentially serious complication or clinical event such as respiratory tract infection, respiratory failure and cardiac arrest. Early identification of changes in RR allows for prompt intervention, whereas failing to detect a change may result in poor patient outcomes. Here, we report on the performance of a depth-sensing camera system for the continuous non-contact 'touchless' monitoring of Respiratory Rate.

methodsSeven healthy subjects undertook a range of breathing rates from 4 to 40 breaths-per-minute (breaths/min). These were set rates of 4, 5, 6, 8, 10, 15, 20, 25, 30, 35 and 40 breaths/min. In total, 553 separate respiratory rate recordings were captured across a range of conditions including body posture, position within the bed, lighting levels and bed coverings. Depth information was acquired from the scene using an Intel D415 RealSense

resultsAn overall RMSD accuracy of 0.69 breaths/min with a corresponding bias of -0.034 was achieved across the target RR range of 4-40 breaths/min. Bland-Altman analysis revealed limits of agreement of -1.42 to 1.36 breaths/min. Three separate sub-ranges of low, normal and high rates, corresponding to < 12, 12-20, > 20 breaths/min, were also examined separately and each found to demonstrate RMSD accuracies of less than one breath-per-minute.

conclusionsWe have demonstrated high accuracy in performance for respiratory rate based on a depth camera system. We have shown the ability to perform well at both high and low rates which are clinically important.

Indexed as

Respiratory RateVital SignsAlgorithmsHumansMonitoring, PhysiologicPostureDepth-sensing camera.Non-contact monitoringRespiratory rate

Identifiers

PMID37010708
PMCPMC10068187

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Registered trials

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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.