Evidence map›Paper›PMID 41090819›Full record

ArticleNanomaterials (Basel, Switzerland)2025

Smart Surface of Steering Wheel Based on Triboelectric Nanogenerator and Artificial Intelligence in Driving Monitoring System.

Fengguang Fan, Shiju E, Mengzhe Kang, Yuting Fan, Qing Song, Yu Xie, Yuankai Zhou, Jiaheng Nie, Xin Cui, Yan Zhang

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Nanomaterials (Basel, Switzerland), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

10 authors.

Fengguang FanCollege of Engineering, Zhejiang Normal University, Jinhua 321004, China.
Shiju ECollege of Engineering, Zhejiang Normal University, Jinhua 321004, China.ORCID 0009-0009-8948-4171
Mengzhe KangBeijing Key Laboratory of High-Entropy Energy Materials and Devices, Beijing Institute of Nanoenergy and Nanosystems, Chinese Academy of Sciences, Beijing 101400, China.
Yuting FanBeijing Key Laboratory of High-Entropy Energy Materials and Devices, Beijing Institute of Nanoenergy and Nanosystems, Chinese Academy of Sciences, Beijing 101400, China.
Qing SongBeijing Key Laboratory of High-Entropy Energy Materials and Devices, Beijing Institute of Nanoenergy and Nanosystems, Chinese Academy of Sciences, Beijing 101400, China.
Yu XieBeijing Key Laboratory of High-Entropy Energy Materials and Devices, Beijing Institute of Nanoenergy and Nanosystems, Chinese Academy of Sciences, Beijing 101400, China.
Yuankai ZhouSchool of Physics, University of Electronic Science and Technology of China, Chengdu 610054, China.
Jiaheng NieSchool of Cybersecurity (Xin Gu Industrial College), Chengdu University of Information Technology, Chengdu 610225, China.
Xin CuiSchool of Materials and Environmental Engineering, Chengdu Technological University, Chengdu 611730, China.
Yan ZhangBeijing Key Laboratory of High-Entropy Energy Materials and Devices, Beijing Institute of Nanoenergy and Nanosystems, Chinese Academy of Sciences, Beijing 101400, China.ORCID 0000-0002-7329-0382

Funding

National Natural Science Foundation of China 52192612National Natural Science Foundation of China U22A2077the Fundamental Research Funds for the Central Universities ZYGX2021YGCX001
6 · The paper itself

Abstract

Real-time driving monitoring systems can use self-powered sensors based on artificial intelligence (AI) and triboelectric nanogenerators (TENGs). Here, we created a TENG-based self-powered intelligent steering wheel that can detect hand gripping. The TENG serves as the steering wheel's smart surface. In addition to monitoring the steering wheel in real time, the intelligent steering wheel reacts quickly. The TENG sensor can detect hazardous conditions and lower processing demands while retaining excellent identification accuracy when used in conjunction with machine learning. Additionally, the TENG sensor may now offer an accurate and affordable monitoring solution for smart driving thanks to the integration of AI.

Indexed as

driving monitoringmachine learningsmart surfacetriboelectric nanogenerator

Identifiers

PMID41090819
PMCPMC12525957

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.