Evidence map›Paper›PMID 40888969›Full record

ArticleNano-micro letters2025

Skin-Inspired Ultra-Linear Flexible Iontronic Pressure Sensors for Wearable Musculoskeletal Monitoring.

Pei Li, Shipan Lang, Lei Xie, Yong Zhang, Xin Gou, Chao Zhang, Chenhui Dong, Chunbao Li, Jun Yang

Abstract read
In one paragraph

Article in Nano-micro letters, 2025. 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
  2. Liquid Metal-Enabled Soft Bioelectronics for Human Health Monitoring.Small (Weinheim an der Bergstrasse, Germany) · 2026
    Review
  3. Article
  4. Review
  5. Review
  6. Article
  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

9 authors.

Pei LiChongqing Institute of Green and Intelligent Technology, Chinese Academy of Sciences, Chongqing, 400714, People's Republic of China.
Shipan LangChongqing Institute of Green and Intelligent Technology, Chinese Academy of Sciences, Chongqing, 400714, People's Republic of China.
Lei XieKey Laboratory of Optoelectronic Technology & Systems (Education Ministry of China), Chongqing University, Chongqing, 400044, People's Republic of China.
Yong ZhangChongqing Institute of Green and Intelligent Technology, Chinese Academy of Sciences, Chongqing, 400714, People's Republic of China.
Xin GouChongqing Institute of Green and Intelligent Technology, Chinese Academy of Sciences, Chongqing, 400714, People's Republic of China.
Chao ZhangChongqing Institute of Green and Intelligent Technology, Chinese Academy of Sciences, Chongqing, 400714, People's Republic of China.
Chenhui DongDepartment of Orthopedics, the Fourth medical center of Chinese PLA General Hospital, Beijing, 100039, People's Republic of China.
Chunbao LiDepartment of Orthopedics, the Fourth medical center of Chinese PLA General Hospital, Beijing, 100039, People's Republic of China. lichunbao301@163.com.
Jun YangChongqing Institute of Green and Intelligent Technology, Chinese Academy of Sciences, Chongqing, 400714, People's Republic of China. jyang@cigit.ac.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The growing prevalence of exercise-induced tibial stress fractures demands wearable sensors capable of monitoring dynamic musculoskeletal loads with medical-grade precision. While flexible pressure-sensing insoles show clinical potential, their development has been hindered by the intrinsic trade-off between high sensitivity and full-range linearity (R

Indexed as

Biomechanical monitoringIontronic sensorLinear rangeLinear sensing factorSkin-inspired design

Identifiers

PMID40888969
PMCPMC12401823

What OpenQuestion holds

Textmetadata
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.