Evidence map›Paper›PMID 35808167›Full record

ArticleSensors (Basel, Switzerland)2022

Wearable Cardiorespiratory Sensors for Aerospace Applications.

Nichakorn Pongsakornsathien, Alessandro Gardi, Yixiang Lim, Roberto Sabatini, Trevor Kistan

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Review
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.

Nichakorn PongsakornsathienSchool of Engineering, RMIT University, Bundoora, VIC 3083, Australia.
Alessandro GardiDepartment of Aerospace Engineering, Khalifa University of Science and Technology, Abu Dhabi 127788, United Arab Emirates.ORCID 0000-0003-4995-4166
Yixiang LimSaab-NTU Joint Lab, Nanyang Technological University, Singapore 639798, Singapore.ORCID 0000-0002-7840-1571
Roberto SabatiniDepartment of Aerospace Engineering, Khalifa University of Science and Technology, Abu Dhabi 127788, United Arab Emirates.ORCID 0000-0002-3399-2291
Trevor KistanSchool of Engineering, RMIT University, Bundoora, VIC 3083, Australia.ORCID 0000-0002-2110-7021

Funding

Northrop Grumman (United States) RE-03163Thales (France) RE-02544
6 · The paper itself

Abstract

Emerging Air Traffic Management (ATM) and avionics human-machine system concepts require the real-time monitoring of the human operator to support novel task assessment and system adaptation features. To realise these advanced concepts, it is essential to resort to a suite of sensors recording neurophysiological data reliably and accurately. This article presents the experimental verification and performance characterisation of a cardiorespiratory sensor for ATM and avionics applications. In particular, the processed physiological measurements from the designated commercial device are verified against clinical-grade equipment. Compared to other studies which only addressed physical workload, this characterisation was performed also looking at cognitive workload, which poses certain additional challenges to cardiorespiratory monitors. The article also addresses the quantification of uncertainty in the cognitive state estimation process as a function of the uncertainty in the input cardiorespiratory measurements. The results of the sensor verification and of the uncertainty propagation corroborate the basic suitability of the commercial cardiorespiratory sensor for the intended aerospace application but highlight the relatively poor performance in respiratory measurements during a purely mental activity.

Indexed as

Aerospace MedicineWearable Electronic DevicesCardiorespiratory FitnessCardiovascular Physiological PhenomenaCognitionElectronic Data ProcessingHumansRespiratory Physiological PhenomenaAir Traffic Managementcardiorespiratorycognitive ergonomicsECGfuzzy systemsheart ratemental workload

Identifiers

PMID35808167
PMCPMC9268781

What OpenQuestion holds

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LicenceCC BY
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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.