Evidence map›Paper›PMID 35323434›Full record

ArticleBiosensors2022

Self-Powered Wearable Biosensor in a Baby Diaper for Monitoring Neonatal Jaundice through a Hydrovoltaic-Biosensing Coupling Effect of ZnO Nanoarray.

Zirui Ning, Zhihe Long, Guangyou Yang, Lili Xing, Xinyu Xue

Abstract read
In one paragraph

Article in Biosensors, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

  1. Article
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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

5 authors.

Zirui NingSchool of Physics, University of Electronic Science and Technology of China, Chengdu 611731, China.
Zhihe LongDepartment of Mechanical Engineering, City University of Hong Kong, 83 Tat Chee Avenue, Kowloon, Hong Kong 999077, China.ORCID 0000-0003-3815-2029
Guangyou YangSchool of Physics, University of Electronic Science and Technology of China, Chengdu 611731, China.
Lili XingSchool of Physics, University of Electronic Science and Technology of China, Chengdu 611731, China.
Xinyu XueSchool of Physics, University of Electronic Science and Technology of China, Chengdu 611731, China.

Funding

Sichuan Science and Technology Program 2020JDJQ0026 and 2021YFG0140
6 · The paper itself

Abstract

Neonatal jaundice refers to the abnormality of bilirubin metabolism for newborns, and wearable transcutaneous bilirubin meters for real-time measuring the bilirubin concentration is an insistent demand for the babies' parents and doctors. In this paper, a self-powered wearable biosensor in a baby diaper for real-time monitoring neonatal jaundice has been realized by the hydrovoltaic-biosensing coupling effect of ZnO nanoarray. Without external power supply, the system can work independently, and the hydrovoltaic output can be treated as both the power source and biosensing signal. The working mechanism is that the hydrovoltaic output arises from the urine flowing on ZnO nanoarray and the enzymatic reaction on the surface can influence the output. The sensing information can be transmitted through a wireless transmitter, and thus the parents and doctors can treat the neonatal jaundice of babies in time. This work can potentially promote the development of next generation of biosensors and physiological monitoring system, and expand the scope of self-powered technique and smart healthcare area.

Indexed as

Biosensing TechniquesJaundice, NeonatalWearable Electronic DevicesZinc OxideElectric Power SuppliesHumansInfant, NewbornZinc Oxidehydrovoltaic effectintelligent diaperneonatal jaundice monitoringself-poweredZnO nanoarray

Identifiers

PMID35323434
PMCPMC8946715

What OpenQuestion holds

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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.