Evidence map›Paper›PMID 41522608›Full record

ArticleResearch (Washington, D.C.)2026

Mantis Leg-Inspired Smart Insole Integrating Closed-Loop Power Supply for Advanced Wearable Gait Diagnostics.

Yingchun Li, Yarong Ding, Yuze Zhang, Xing Guo, Kaixin Lei, Jiachun Sun, Xing Hu, Xinyue Li, Wenguang Yang, Rui Liu and 12 more

Abstract read
In one paragraph

Article in Research (Washington, D.C.), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Article
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

22 authors.

Yingchun LiAdvanced Interdisciplinary Research Center for Flexible Electronics, Academy of Advanced Interdisciplinary Research, Xidian University, Xi'an 710071, P.R. China.
Yarong DingState Key Laboratory of Wide-Bandgap Semiconductor Devices and Integrated Technology, Faculty of Integrated Circuit, Xidian University, Xi'an 710071, P.R. China.
Yuze ZhangInstitute of Electromechanical Science and Technology, Xidian University, Xi'an 710071, P.R. China.
Xing GuoAdvanced Interdisciplinary Research Center for Flexible Electronics, Academy of Advanced Interdisciplinary Research, Xidian University, Xi'an 710071, P.R. China.
Kaixin LeiInstitute of Electromechanical Science and Technology, Xidian University, Xi'an 710071, P.R. China.
Jiachun SunAdvanced Interdisciplinary Research Center for Flexible Electronics, Academy of Advanced Interdisciplinary Research, Xidian University, Xi'an 710071, P.R. China.
Xing HuState Key Laboratory of Wide-Bandgap Semiconductor Devices and Integrated Technology, Faculty of Integrated Circuit, Xidian University, Xi'an 710071, P.R. China.
Xinyue LiState Key Laboratory of Wide-Bandgap Semiconductor Devices and Integrated Technology, Faculty of Integrated Circuit, Xidian University, Xi'an 710071, P.R. China.
Wenguang YangState Key Laboratory of Wide-Bandgap Semiconductor Devices and Integrated Technology, Faculty of Integrated Circuit, Xidian University, Xi'an 710071, P.R. China.
Rui LiuDepartment of Rehabilitation Medicine, Tangdu Hospital, Air Force Military Medical University, Xi'an 710032, P.R. China.
Zhenhua LinState Key Laboratory of Wide-Bandgap Semiconductor Devices and Integrated Technology, Faculty of Integrated Circuit, Xidian University, Xi'an 710071, P.R. China.
Wendong ZhangDepartment of Rehabilitation Medicine, Tangdu Hospital, Air Force Military Medical University, Xi'an 710032, P.R. China.
Shaozhe TanState Key Laboratory of Wide-Bandgap Semiconductor Devices and Integrated Technology, Faculty of Integrated Circuit, Xidian University, Xi'an 710071, P.R. China.
Xu YangShaanxi Key Laboratory of Degradable Biomedical Materials, School of Chemical Engineering, Northwest University, Xi'an 710069, P.R. China.
Yumeng XuState Key Laboratory of Wide-Bandgap Semiconductor Devices and Integrated Technology, Faculty of Integrated Circuit, Xidian University, Xi'an 710071, P.R. China.
Jin TianThe Key Laboratory of Biomedical Information Engineering of Ministry of Education, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an 710049, P.R. China.
Bokun ZhangThe Key Laboratory of Biomedical Information Engineering of Ministry of Education, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an 710049, P.R. China.
Yue HaoState Key Laboratory of Wide-Bandgap Semiconductor Devices and Integrated Technology, Faculty of Integrated Circuit, Xidian University, Xi'an 710071, P.R. China.
Xiangning LiInstitute of Electromechanical Science and Technology, Xidian University, Xi'an 710071, P.R. China.
Yannan LiuShaanxi Key Laboratory of Degradable Biomedical Materials, School of Chemical Engineering, Northwest University, Xi'an 710069, P.R. China.
Feng XuThe Key Laboratory of Biomedical Information Engineering of Ministry of Education, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an 710049, P.R. China.
Jingjing ChangAdvanced Interdisciplinary Research Center for Flexible Electronics, Academy of Advanced Interdisciplinary Research, Xidian University, Xi'an 710071, P.R. China.ORCID https://orcid.org/0000-0003-3773-182X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Precise diagnosis and management of lower extremity dysfunction disorders hinge on continuous gait monitoring. Nevertheless, the existing wearable devices fall short as they grapple with insufficient sensing precision, inadequate energy endurance, and ineffective intelligent data analysis. Here, we report a fully integrated, biomimetic smart insole that incorporates 3 synergistic innovations to overcome these challenges. First, inspired by the hierarchical mechanosensory apparatus of mantis legs, we design dual-microstructure capacitive sensors with a detection limit of 0.10 Pa and a maximum detection range of 1.4 MPa. This sensor can distinguish pressures across a wide range from subtle to substantial and exhibits robust mechanical stability over 12,000 cycles, making it highly suitable for insole applications and outperforming current flexible pressure sensors. Second, we realize energy-autonomous operation by integrating nano-perovskite solar cells with high-capacity lithium-sulfur nanobatteries, achieving an average photocharging efficiency of 11.21% and energy storage efficiency of 72.15%. Third, embedded artificial intelligence algorithms interpret the spatiotemporal pressure data transmitted via a 16-channel wireless module. These models achieve 96.0% accuracy in detecting foot arch abnormalities and 97.6% accuracy in classifying 12 pathological gait patterns. Collectively, these 3 advances, including bioinspired high-resolution sensing, sustainable energy interfacing, and intelligent mechanodiagnosis, establish a closed-loop wearable platform validated in clinical studies. This system offers promising applications in early disease screening, personalized rehabilitation, and remote healthcare.

Identifiers

PMID41522608
PMCPMC12779891

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.