Evidence map›Paper›PMID 37206201›Full record

ArticleBioengineering & translational medicine2023

An ultralow power wearable vital sign sensor using an electromagnetically reactive near field.

Seoktae Seo, Hyunkyeong Jo, Jungho Kim, Bonyoung Lee, Franklin Bien

Abstract read
In one paragraph

Article in Bioengineering & translational medicine, 2023. 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. 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.

Seoktae SeoDepartment of Electrical Engineering Ulsan National Institute of Science and Technology Ulsan Republic of Korea.ORCID https://orcid.org/0000-0002-1258-9874
Hyunkyeong JoDepartment of Electrical Engineering Ulsan National Institute of Science and Technology Ulsan Republic of Korea.ORCID https://orcid.org/0000-0003-4397-5556
Jungho KimDepartment of Electrical Engineering Ulsan National Institute of Science and Technology Ulsan Republic of Korea.
Bonyoung LeeDepartment of Electrical Engineering Ulsan National Institute of Science and Technology Ulsan Republic of Korea.
Franklin BienDepartment of Electrical Engineering Ulsan National Institute of Science and Technology Ulsan Republic of Korea.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Despite coronavirus disease 2019, cardiovascular disease, the leading cause of global death, requires timely detection and treatment for a high survival rate, underscoring the 24 h monitoring of vital signs. Therefore, telehealth using wearable devices with vital sign sensors is not only a fundamental response against the pandemic but a solution to provide prompt healthcare for the patients in remote sites. Former technologies which measured a couple of vital signs had features that disturbed practical applications to wearable devices, such as heavy power consumption. Here, we suggest an ultralow power (100 μW) sensor that collects all cardiopulmonary vital signs, including blood pressure, heart rate, and the respiration signal. The small and lightweight (2 g) sensor designed to be easily embedded in the flexible wristband generates an electromagnetically reactive near field to monitor the contraction and relaxation of the radial artery. The proposed ultralow power sensor measuring noninvasively continuous and accurate cardiopulmonary vital signs at once will be one of the most promising sensors for wearable devices to bring telehealth to our lives.

Indexed as

bioelectronicsbiosensorreactive near fieldultralow power consumptionvital sign sensorwearable sensor

Identifiers

PMID37206201
PMCPMC10189444

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.