Evidence map›Paper›PMID 42018619›Full record

ArticleScience advances2026

Biomimetic metamaterial-based interface for decoding heterogeneous mechanodermal activity.

Muzi Xu, Jiaqi Zhang, Chaoqun Dong, Zibo Zhang, Duanyang Li, Wentian Yi, Miaomiao Zou, Chenyu Tang, George G Malliaras, Luigi G Occhipinti

Abstract read
In one paragraph

Article in Science advances, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0cells of the map it votes in
0citing papers in PubMed
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1 · What the graph read from it

What it found

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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

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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

10 authors.

Muzi XuElectrical Engineering Division, Department of Engineering, University of Cambridge, Cambridge CB3 0FA, UK.ORCID 0000-0001-6381-9863
Jiaqi ZhangDepartment of Electrical and Electronic Engineering, University of Hong Kong, Pokfulam Road, Hong Kong SAR 999077, China.ORCID 0009-0006-9479-5706
Chaoqun DongElectrical Engineering Division, Department of Engineering, University of Cambridge, Cambridge CB3 0FA, UK.ORCID 0000-0001-6433-3478
Zibo ZhangElectrical Engineering Division, Department of Engineering, University of Cambridge, Cambridge CB3 0FA, UK.ORCID 0009-0000-3685-9069
Duanyang LiElectrical Engineering Division, Department of Engineering, University of Cambridge, Cambridge CB3 0FA, UK.
Wentian YiElectrical Engineering Division, Department of Engineering, University of Cambridge, Cambridge CB3 0FA, UK.
Miaomiao ZouInstitute for Manufacturing, Department of Engineering, University of Cambridge, Cambridge CB3 0FS, UK.
Chenyu TangElectrical Engineering Division, Department of Engineering, University of Cambridge, Cambridge CB3 0FA, UK.ORCID 0000-0002-6368-5639
George G MalliarasElectrical Engineering Division, Department of Engineering, University of Cambridge, Cambridge CB3 0FA, UK.ORCID 0000-0002-4582-8501
Luigi G OcchipintiElectrical Engineering Division, Department of Engineering, University of Cambridge, Cambridge CB3 0FA, UK.ORCID 0000-0002-9067-2534

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The human skin acts as a dynamic biomechanical interface that conveys critical physiological and behavioral information through spatiotemporally distributed deformations. Because of the limited capabilities of current sensing technologies, the spatiotemporal diversity of its mechanical cues has remained underused to date, preventing these mechanisms from being used to capture and decode the full spectrum of underlying physiological states. In this work, we define this heterogeneous set of mechanical signals as mechanodermal activity (MDA) and introduce the biomimetic metamaterial-based interface (BMMI), an engineered auxetic metamaterial substrate that reproduces the microrelief and mechanoreceptor architecture of natural skin. The BMMI allows selective capture of diverse MDA signals from adjacent skin regions with simultaneous signal amplification and noise suppression and permits straightforward modulation to accommodate various scenarios. Combined with bespoke algorithms, the wireless BMMI device decodes MDA accurately and robustly for multimodal communication interfaces, unleashing applications in health care monitoring and human-machine interaction.

Indexed as

Biomimetic MaterialsBiomimeticsMechanoreceptorsSkinAlgorithmsHumans

Identifiers

PMID42018619
PMCPMC13101874

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.