Evidence map›Paper›PMID 38749008›Full record

ArticleAdvanced science (Weinheim, Baden-Wurttemberg, Germany)2024

Scalable and Ultra-Sensitive Nanofibers Coaxial Yarn-Woven Triboelectric Nanogenerator Textile Sensors for Real-Time Gait Analysis.

Yihan Wang, Lang Chu, Si Meng, Mingxuan Yang, Yidan Yu, Xiaokang Deng, Cheng Qi, Tiantian Kong, Zhou Liu

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Advanced science (Weinheim, Baden-Wurttemberg, Germany), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing 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

14 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

9 authors.

Yihan WangDepartment of Biomedical Engineering, School of Medicine, Shenzhen University, Shenzhen, Guangdong, 518000, China.
Lang ChuDepartment of Biomedical Engineering, School of Medicine, Shenzhen University, Shenzhen, Guangdong, 518000, China.
Si MengCollege of Chemistry and Environmental Engineering, Shenzhen University, Shenzhen, Guangdong, 518000, China.
Mingxuan YangCollege of Chemistry and Environmental Engineering, Shenzhen University, Shenzhen, Guangdong, 518000, China.
Yidan YuCollege of Chemistry and Environmental Engineering, Shenzhen University, Shenzhen, Guangdong, 518000, China.
Xiaokang DengCollege of Chemistry and Environmental Engineering, Shenzhen University, Shenzhen, Guangdong, 518000, China.
Cheng QiGuangdong Provincial Key Laboratory of Micro/Nano Optomechatronics Engineering, College of Mechatronics and Control Engineering, Shenzhen University, Shenzhen, Guangdong, 518000, China.
Tiantian KongDepartment of Biomedical Engineering, School of Medicine, Shenzhen University, Shenzhen, Guangdong, 518000, China.
Zhou LiuDepartment of Biomedical Engineering, School of Medicine, Shenzhen University, Shenzhen, Guangdong, 518000, China.

Funding

Basic and Applied Basic Research Foundation of Guangdong Province 2022A1515110246Basic and Applied Basic Research Foundation of Guangdong Province 2023A1515011827Innovative Research Group Project of the National Natural Science Foundation of China 22078197Innovative Research Group Project of the National Natural Science Foundation of China 22308219Innovative Research Group Project of the National Natural Science Foundation of China 22322808Innovative Research Group Project of the National Natural Science Foundation of China 52172283Natural Science Foundation of Guangdong Province 2021A1515012506Shenzhen Science and Technology Innovation Program 20220810120421001Shenzhen Science and Technology Innovation Program JCYJ20220818095801003Shenzhen Science and Technology Innovation Program RCYX20221008092902010
6 · The paper itself

Abstract

Yarn-woven triboelectric nanogenerators (TENGs) have greatly advanced wearable sensor technology, but their limited sensitivity and stability hinder broad adoption. To address these limitations, Poly(VDF-TrFE) and P(olyadiohexylenediamine (PA66)-based nanofibers coaxial yarns (NCYs) combining coaxial conjugated electrospinning and online conductive adhesive coating are developed. The integration of these NCYs led to enhanced TENGs (NCY-TENGs), notable for their flexibility, stretchability, and improved sensitivity, which is ideal for capturing body motion signals. One significant application of this technology is the fabrication of smart insoles from NCY-TENG plain-woven fabrics. These insoles are highly sensitive and possess antibacterial, breathable, and washable properties, making them ideal for real-time gait monitoring in patients with diabetic foot conditions. The NCY-TENGs and their derivatives show immense potential for a variety of wearable electronic devices, representing a considerable advancement in the field of wearable sensors.

Indexed as

GaitNanofibersTextilesWearable Electronic DevicesDiabetic FootEquipment DesignHumansNanotechnologybiomedical applicationscoaxial yarnselectrospinningtriboelectric nanogeneratorswearable devices

Identifiers

PMID38749008
PMCPMC11267306

What OpenQuestion holds

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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.