Evidence map›Paper›PMID 40238890›Full record

ArticleScience advances2025

A wireless, self-powered smart insole for gait monitoring and recognition via nonlinear synergistic pressure sensing.

Qi Wang, Hui Guan, Chen Wang, Peiming Lei, Hongwei Sheng, Huasheng Bi, Jinkun Hu, Chenhui Guo, Yichuan Mao, Jiao Yuan and 4 more

Abstract read
In one paragraph

Article in Science advances, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
27citing papers in PubMed, 1 pooled it
–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

27 citing papers in PubMed, 1 synthesis or guideline pooled it.

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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

14 authors.

Qi WangSchool of Physical Science and Technology, Lanzhou University, Lanzhou, Gansu 730000, China.ORCID 0009-0003-5858-140X
Hui GuanSchool of Physical Science and Technology, Lanzhou University, Lanzhou, Gansu 730000, China.
Chen WangSchool of Physical Science and Technology, Lanzhou University, Lanzhou, Gansu 730000, China.ORCID 0000-0003-1747-335X
Peiming LeiSchool of Physical Science and Technology, Lanzhou University, Lanzhou, Gansu 730000, China.ORCID 0009-0008-4650-9239
Hongwei ShengSchool of Physical Science and Technology, Lanzhou University, Lanzhou, Gansu 730000, China.ORCID 0000-0003-3136-4379
Huasheng BiSchool of Physical Science and Technology, Lanzhou University, Lanzhou, Gansu 730000, China.
Jinkun HuSchool of Physical Science and Technology, Lanzhou University, Lanzhou, Gansu 730000, China.ORCID 0009-0000-4957-509X
Chenhui GuoSchool of Physical Science and Technology, Lanzhou University, Lanzhou, Gansu 730000, China.
Yichuan MaoSchool of Physical Science and Technology, Lanzhou University, Lanzhou, Gansu 730000, China.
Jiao YuanSchool of Physical Science and Technology, Lanzhou University, Lanzhou, Gansu 730000, China.
Mingjiao ShaoSchool of Physical Science and Technology, Lanzhou University, Lanzhou, Gansu 730000, China.
Zhiwen JinSchool of Physical Science and Technology, Lanzhou University, Lanzhou, Gansu 730000, China.ORCID 0000-0002-5256-9106
Jinghua LiDepartment of Materials Science and Engineering, The Ohio State University, Columbus, OH 43210, USA.ORCID 0000-0001-8985-566X
Wei LanSchool of Physical Science and Technology, Lanzhou University, Lanzhou, Gansu 730000, China.ORCID 0000-0001-6194-4839

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Wearable insole-based pressure sensor systems have gained attention for continuous gait monitoring, showing potential for preventing, diagnosing, and treating conditions such as lumbar degenerative disease and diabetic foot ulcers. However, challenges such as nonlinear response, low stability, and energy limitations have hindered widespread adoption. Here, we report a fully integrated, self-powered, wireless smart insole designed for plantar pressure monitoring and real-time visualization and analysis of gait. The pressure sensor uses a nonlinear synergistic strategy, achieving remarkable linearity (

Indexed as

GaitWearable Electronic DevicesWireless TechnologyBiomechanical PhenomenaHumansMonitoring, PhysiologicPressureSmartphone

Identifiers

PMID40238890
PMCPMC12002114

What OpenQuestion holds

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LicenceCC BY-NC
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Registered trials

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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.