Evidence map›Paper›PMID 39523417›Full record

ArticleScientific reports2024

Novel metrics for tracking blood pressure changes incontinuous cuffless blood pressure estimations.

Shan He, Miodrag Bolić

Abstract read
In one paragraph

Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

2 authors.

Shan HeHealth Devices Research Group, School of Electrical Engineering and Computer Science, Faculty of Engineering, University of Ottawa, Ottawa, K1N 6N5, Canada. she014@uottawa.ca.
Miodrag BolićHealth Devices Research Group, School of Electrical Engineering and Computer Science, Faculty of Engineering, University of Ottawa, Ottawa, K1N 6N5, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Recent studies revealed the importance of tracking continuous blood pressure (BP) changes in monitoring and controlling hypertension and diagnosing cardiovascular diseases. However, current evaluation protocols utilize distance measures as primary metrics, which cannot properly evaluate the ability of the estimation model to track BP changes. This paper proposes a comprehensive evaluation framework which evaluates the distance and trend similarity metrics, and the composite metric of both between the reference and estimated BPs. The results of applying both widely used conventional metrics and the new proposed metrics for BP estimations are demonstrated in an example of comparing the reference with a set of different BP estimations. Then, the metrics are applied to BP estimations obtained using state-of-the-art (SOTA) algorithms. It is shown that even though SOTA algorithms have a low mean and standard deviation of absolute difference, they are not capable of tracking short-term blood pressure changes. Additionally, the proposed metrics are normalized metrics and range from -1 to 1, making them intuitively interpretable, similar to well-known correlation coefficients. Therefore, we suggest that the proposed evaluation framework should be used regularly in evaluating continuous BP monitoring systems.

Indexed as

AlgorithmsBlood PressureBlood Pressure DeterminationFemaleHumansHypertensionMale

Identifiers

PMID39523417
PMCPMC11551165

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.