Evidence map›Paper›PMID 42491612›Full record

ArticleiScience2026

A self-powered corrugated paper structure triboelectric sensor with deep learning for table tennis motion identification.

Xiaoping Zhang, Tian Tian

Abstract read
In one paragraph

Article in iScience, 2026. 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

2 authors.

Xiaoping ZhangSouth China Agricultural University, Department of Physical Education, Guangzhou 510642, China.
Tian TianSouth China Agricultural University, Department of Physical Education, Guangzhou 510642, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Intelligent sports equipment has attracted increasing attention for quantitative performance evaluation and personalized training. Here, a corrugated paper-based triboelectric nanogenerator (CP-TENG) is developed for mechanical energy harvesting and table tennis motion sensing, combined with artificial intelligence-assisted signal recognition. A dielectric enhancement strategy is implemented using poly(vinylidene fluoride)/lead zirconate titanate (Pb(Zr,Ti)O

Indexed as

artificial intelligence, AIintelligent sports monitoringPVDF/PZT compositeself-powered sensing systemtriboelectric nanogenerators, TENGs

Identifiers

PMID42491612
PMCPMC13378346

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.