Evidence map›Paper›PMID 37968442›Full record

ArticleScientific reports2023

Variable sensitivity multimaterial robotic e-skin combining electronic and ionic conductivity using electrical impedance tomography.

Aleix Costa Cornellà, David Hardman, Leone Costi, Joost Brancart, Guy Van Assche, Fumiya Iida

Abstract read
In one paragraph

Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Toward Autonomous Self-Healing in Soft Robotics: A Review and Perspective for Future Research.Advanced intelligent systems (Weinheim an der Bergstrasse, Germany) · 2025
    Review
  2. Review
  3. 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

6 authors.

Aleix Costa CornellàPhysical Chemistry and Polymer Science, Vrije Universiteit Brussel, 1050, Brussels, Belgium.
David HardmanBio-Inspired Robotics Lab, University of Cambridge, Cambridge, CB2 1PZ, UK.
Leone CostiBio-Inspired Robotics Lab, University of Cambridge, Cambridge, CB2 1PZ, UK.
Joost BrancartPhysical Chemistry and Polymer Science, Vrije Universiteit Brussel, 1050, Brussels, Belgium.
Guy Van AsschePhysical Chemistry and Polymer Science, Vrije Universiteit Brussel, 1050, Brussels, Belgium.
Fumiya IidaBio-Inspired Robotics Lab, University of Cambridge, Cambridge, CB2 1PZ, UK. fi224@cam.ac.uk.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Electronic skins (e-skins) aim to replicate the capabilities of human skin by integrating electronic components and advanced materials into a flexible, thin, and stretchable substrate. Electrical impedance tomography (EIT) has recently been adopted in the area of e-skin thanks to its robustness and simplicity of fabrication compared to previous methods. However, the most common EIT configurations have limitations in terms of low sensitivities in areas far from the electrodes. Here we combine two piezoresistive materials with different conductivities and charge carriers, creating anisotropy in the sensitive part of the e-skin. The bottom layer consists of an ionically conducting hydrogel, while the top layer is a self-healing composite that conducts electrons through a percolating carbon black network. By changing the pattern of the top layer, the resulting distribution of currents in the e-skin can be tuned to locally adapt the sensitivity. This approach can be used to biomimetically adjust the sensitivities of different regions of the skin. It was demonstrated how the sensitivity increased by 500% and the localization error reduced by 40% compared to the homogeneous case, eliminating the lower sensitivity regions. This principle enables integrating the various sensing capabilities of our skins into complex 3D geometries. In addition, both layers of the developed e-skin have self-healing capabilities, showing no statistically significant difference in localization performance before the damage and after healing. The self-healing bilayer e-skin could recover full sensing capabilities after healing of severe damage.

Indexed as

Robotic Surgical ProceduresElectric ConductivityElectric ImpedanceElectronicsHumansTomography

Identifiers

PMID37968442
PMCPMC10651849

What OpenQuestion 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 OpenQuestion graph.