Evidence map›Paper›PMID 41400122›Full record

ArticleAdvanced science (Weinheim, Baden-Wurttemberg, Germany)2026

Thermo-Responsive Self-Recoverable Porous Sensors with Writable Electrodes: Advancing Wearable Motion Detection.

Ying Gao, Xingyi Dai, Yuanyuan Zhang, Guohao Fang, Gui Li, Yu Zheng, Long-Biao Huang, Biqin Dong

Abstract read
In one paragraph

Article in Advanced science (Weinheim, Baden-Wurttemberg, Germany), 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

8 authors.

Ying GaoSchool of Environment and Civil Engineering, Guangdong Provincial Key Laboratory of Intelligent Disaster Prevention and Emergency Technologies for Urban Lifeline Engineering, Dongguan University of Technology, Dongguan, 523808, P. R. China.ORCID https://orcid.org/0000-0003-0693-8262
Xingyi DaiKey Laboratory of Optoelectronic Devices and Systems of Ministry of Education and Guangdong Province, College of Physics and Optoelectronic Engineering, Shenzhen University, Shenzhen, 518060, P. R. China.
Yuanyuan ZhangCollege of Civil and Transportation Engineering, Guangdong Province Key Laboratory of Durability for Marine Civil Engineering, The Key Laboratory on Durability of Civil Engineering in Shenzhen, Shenzhen University, Shenzhen, 518060, P. R. China.
Guohao FangInstitute for Advanced Study, Shenzhen University, Shenzhen, 518060, P. R. China.
Gui LiSchool of Environment and Civil Engineering, Guangdong Provincial Key Laboratory of Intelligent Disaster Prevention and Emergency Technologies for Urban Lifeline Engineering, Dongguan University of Technology, Dongguan, 523808, P. R. China.
Yu ZhengSchool of Environment and Civil Engineering, Guangdong Provincial Key Laboratory of Intelligent Disaster Prevention and Emergency Technologies for Urban Lifeline Engineering, Dongguan University of Technology, Dongguan, 523808, P. R. China.
Long-Biao HuangKey Laboratory of Optoelectronic Devices and Systems of Ministry of Education and Guangdong Province, College of Physics and Optoelectronic Engineering, Shenzhen University, Shenzhen, 518060, P. R. China.ORCID https://orcid.org/0009-0002-5853-645X
Biqin DongCollege of Civil and Transportation Engineering, Guangdong Province Key Laboratory of Durability for Marine Civil Engineering, The Key Laboratory on Durability of Civil Engineering in Shenzhen, Shenzhen University, Shenzhen, 518060, P. R. China.

Funding

Guang dong Provincial Key Laboratory of Marine Civil Engineering (SZU) 2020B1212060074Guangdong Provincial Science and Technology Plan Project 2025A0505010022National Key R&D Program of China 2024YFE0201900National Natural Science Foundation of China 51925805National Natural Science Foundation of China 52208272Natural Science Foundation of Guangdong Province 2024A1515010639Shenzhen Key Laboratory for Low-carbon Construction Material and Technology ZDSYS20220606100406016
6 · The paper itself

Abstract

The remarkable applications of flexible and wearable sensors in the fields of human motion detection and health monitoring have attracted extensive attention from academic and industrial pools. However, creating advanced sensors capable of self-recovery, shape-editability, and multi-mode for long-term motion detection still remains challenging. Herein, a self-recoverable flexible porous sensor with diverse designability of electrodes is developed for comprehensive motion detection. Shape memory polymer (SMP) is utilized as a core material to manufacture the porous electrodes, which endows the sensor with excellent self-recoverability, enhanced structural robustness, and high flexibility. The porous electrodes further enable dual triboelectric and piezoresistive sensing modes, which can achieve versatile detection capabilities for various body movements and motion patterns. A writable vapor phase polymerization technique is employed to realize the shape-editability of the electrodes, ensuring adaptability to diverse body shapes and complex movements. The novel sensors are integrated into smart insoles, joint monitoring bands, and intelligent gloves, demonstrating the capabilities of the sensors in plantar pressure monitoring, joint motion tracking, tactile sensing, and information interaction. This work offers a promising strategy for the development of advanced wearable sensors with improved sustainability, reliability, and conformability.

Indexed as

Wearable Electronic DevicesElectrodesEquipment DesignHumansMonitoring, PhysiologicMotionMovementPorosityDual‐modesHuman motion detectionSelf‐recoveringShape‐editabilityShape memory polymer

Identifiers

PMID41400122
PMCPMC12948277

What OpenQuestion holds

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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.