Evidence map›Paper›PMID 38907374›Full record

ArticleJMIR biomedical engineering2021

Wearable Bioimpedance Monitoring: Viewpoint for Application in Chronic Conditions.

Willemijn Groenendaal, Seulki Lee, Chris van Hoof

Abstract read
In one paragraph

Article in JMIR biomedical engineering, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing 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

19 citing papers in PubMed.

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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

3 authors.

Willemijn GroenendaalImec the Netherlands / Holst Centre, Eindhoven, Netherlands.ORCID https://orcid.org/0000-0003-1024-0756
Seulki LeeImec the Netherlands / Holst Centre, Eindhoven, Netherlands.ORCID https://orcid.org/0000-0003-4900-2085
Chris van HoofImec, Leuven, Belgium.ORCID https://orcid.org/0000-0002-4645-3326

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Currently, nearly 6 in 10 US adults are suffering from at least one chronic condition. Wearable technology could help in controlling the health care costs by remote monitoring and early detection of disease worsening. However, in recent years, there have been disappointments in wearable technology with respect to reliability, lack of feedback, or lack of user comfort. One of the promising sensor techniques for wearable monitoring of chronic disease is bioimpedance, which is a noninvasive, versatile sensing method that can be applied in different ways to extract a wide range of health care parameters. Due to the changes in impedance caused by either breathing or blood flow, time-varying signals such as respiration and cardiac output can be obtained with bioimpedance. A second application area is related to body composition and fluid status (eg, pulmonary congestion monitoring in patients with heart failure). Finally, bioimpedance can be used for continuous and real-time imaging (eg, during mechanical ventilation). In this viewpoint, we evaluate the use of wearable bioimpedance monitoring for application in chronic conditions, focusing on the current status, recent improvements, and challenges that still need to be tackled.

Indexed as

bioimpedancebody compositionimagingimpedance cardiographyimpedance pneumographywearable monitoring

Identifiers

PMID38907374
PMCPMC11041432

What Socratic 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 Socratic graph.