Evidence map›Paper›PMID 36551094›Full record

ReviewBiosensors2022

Adaptive Triboelectric Nanogenerators for Long-Term Self-Treatment: A Review.

Zequan Zhao, Yin Lu, Yajun Mi, Jiajing Meng, Xueqing Wang, Xia Cao, Ning Wang

Abstract readReview
In one paragraph

Review in Biosensors, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Review
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  7. 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

7 authors.

Zequan ZhaoCenter for Green Innovation, School of Mathematics and Physics, University of Science and Technology Beijing, Beijing 100083, China.
Yin LuCenter for Green Innovation, School of Mathematics and Physics, University of Science and Technology Beijing, Beijing 100083, China.
Yajun MiCenter for Green Innovation, School of Mathematics and Physics, University of Science and Technology Beijing, Beijing 100083, China.
Jiajing MengCenter for Green Innovation, School of Mathematics and Physics, University of Science and Technology Beijing, Beijing 100083, China.
Xueqing WangCenter for Green Innovation, School of Mathematics and Physics, University of Science and Technology Beijing, Beijing 100083, China.
Xia CaoBeijing Institute of Nanoenergy and Nanosystems, Chinese Academy of Sciences, Beijing 100083, China.
Ning WangCenter for Green Innovation, School of Mathematics and Physics, University of Science and Technology Beijing, Beijing 100083, China.ORCID 0000-0001-9772-7270

Funding

the Fundamental Research Funds for the Central Universities No. FRF-MP-20-38the National Natural Science Foundation of China NSFC Nos. 51873020
6 · The paper itself

Abstract

Triboelectric nanogenerators (TENGs) were initially invented as an innovative energy-harvesting technology for scavenging mechanical energy from our bodies or the ambient environment. Through adaptive customization design, TENGs have also become a promising player in the self-powered wearable medical market for improving physical fitness and sustaining a healthy lifestyle. In addition to simultaneously harvesting our body's mechanical energy and actively detecting our physiological parameters and metabolic status, TENGs can also provide personalized medical treatment solutions in a self-powered modality. This review aims to cover the recent advances in TENG-based electronics in clinical applications, beginning from the basic working principles of TENGs and their general operation modes, continuing to the harvesting of bioenergy from the human body, and arriving at their adaptive design toward applications in chronic disease diagnosis and long-term clinical treatment. Considering the highly personalized usage scenarios, special attention is paid to customized modules that are based on TENGs and support complex medical treatments, where sustainability, biodegradability, compliance, and bio-friendliness may be critical for the operation of clinical systems. While this review provides a comprehensive understanding of TENG-based clinical devices that aims to reach a high level of technological readiness, the challenges and shortcomings of TENG-based clinical devices are also highlighted, with the expectation of providing a useful reference for the further development of such customized healthcare systems and the transfer of their technical capabilities into real-life patient care.

Indexed as

ElectronicsResearch DesignHumansTechnologyadaptivityclinical treatmentself-diagnosisself-powered devicetriboelectric nanogenerator

Identifiers

PMID36551094
PMCPMC9775114

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.