Evidence map›Paper›PMID 42094101›Full record

ArticleNational science review2026

A scalable, hyperstable intelligent fibre velocimeter for dynamic digitization of resistance training.

Jingyu Ouyang, Pan Li, Yuqi Zou, Guangcong Liu, Hongtao Zeng, Rui Han, Duo Li, Weitao Zheng, Jingbo Sun, Guangming Tao

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in National science review, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

10 authors.

Jingyu OuyangResearch Center for Intelligent Fiber Devices and Equipment, State Key Laboratory of New Textile Materials and Advanced Processing, School of Physical Education, Wuhan National Laboratory for Optoelectronics, School of Materials Science and Engineering, Department of Geriatrics, Department of Orthopedics, and Key Laboratory of Vascular Aging, Ministry of Education, Tongji Hospital of Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430074, China.
Pan LiCenter for Intelligent Health Interdisciplinary Science, Central China Normal University, Wuhan 430079, China.
Yuqi ZouCenter for Intelligent Health Interdisciplinary Science, Central China Normal University, Wuhan 430079, China.
Guangcong LiuResearch Center for Intelligent Fiber Devices and Equipment, State Key Laboratory of New Textile Materials and Advanced Processing, School of Physical Education, Wuhan National Laboratory for Optoelectronics, School of Materials Science and Engineering, Department of Geriatrics, Department of Orthopedics, and Key Laboratory of Vascular Aging, Ministry of Education, Tongji Hospital of Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430074, China.
Hongtao ZengResearch Center for Intelligent Fiber Devices and Equipment, State Key Laboratory of New Textile Materials and Advanced Processing, School of Physical Education, Wuhan National Laboratory for Optoelectronics, School of Materials Science and Engineering, Department of Geriatrics, Department of Orthopedics, and Key Laboratory of Vascular Aging, Ministry of Education, Tongji Hospital of Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430074, China.
Rui HanKey Laboratory of Sports Engineering of General Administration of Sport of China, Wuhan Sports University, Wuhan 430079, China.
Duo LiKey Laboratory of Sports Engineering of General Administration of Sport of China, Wuhan Sports University, Wuhan 430079, China.
Weitao ZhengKey Laboratory of Sports Engineering of General Administration of Sport of China, Wuhan Sports University, Wuhan 430079, China.
Jingbo SunResearch Center for Intelligent Fiber Devices and Equipment, State Key Laboratory of New Textile Materials and Advanced Processing, School of Physical Education, Wuhan National Laboratory for Optoelectronics, School of Materials Science and Engineering, Department of Geriatrics, Department of Orthopedics, and Key Laboratory of Vascular Aging, Ministry of Education, Tongji Hospital of Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430074, China.
Guangming TaoResearch Center for Intelligent Fiber Devices and Equipment, State Key Laboratory of New Textile Materials and Advanced Processing, School of Physical Education, Wuhan National Laboratory for Optoelectronics, School of Materials Science and Engineering, Department of Geriatrics, Department of Orthopedics, and Key Laboratory of Vascular Aging, Ministry of Education, Tongji Hospital of Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430074, China.ORCID https://orcid.org/0000-0002-1371-7735

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Real-time accuracy and continuous dynamic monitoring capability of devices are crucial for the scientific configuration and dynamic modulation of resistance training, such as strength training, rehabilitation and in-orbit training for astronauts. However, developing monitoring devices capable of providing real-time, accurate and dynamic quantification for high-velocity resistance training remains a notable challenge. Here, we present a scalable and hyperstable intelligent fibre velocimeter designed for the digital, real-time and dynamic monitoring of resistance training. By incorporating the fibre velocimeter as a core component, the intelligent resistance band system demonstrates cyclic stability exceeding 120 000 cycles and torsional insensitivity, facilitating hyperstable velocimetry within the 0-2.5 m/s range with an accuracy exceeding 95%. This system is capable of capturing instantaneous training parameters, including velocity, tension and power during cyclic resistance training, as well as performing dynamic evaluations and providing early warnings for overspeed or fatigue. A comparative experiment with and without feedback guidance from the intelligent resistance band system verified that its precise feedback significantly elevates training intensity, explosive performance and movement compliance while reducing injury risk. Given its compact design, real-time sensing and evaluation of highly accurate multidimensional training parameters, and hyperstability, this system potentially advances training digitization and sports intelligence.

Indexed as

fibre sensortraining digitizationvelocity measurement

Identifiers

PMID42094101
PMCPMC13142149

What Socratic 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 Socratic graph.