Evidence map›Paper›PMID 42420293›Full record

ArticleNature communications2026

Body surface potential mapping of the cortico-muscular axis using smart textile electrode arrays.

Ruben Ruiz-Mateos Serrano, Charlie Brunt, Xudong Tao, Maciej Zajaczkowski, Antonio Dominguez-Alfaro, Matias L Picchio, Daniele Mantione, Emmanuel M Drakakis, David Mecerreyes, George G Malliaras

Abstract read
In one paragraph

Article in Nature communications, 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

10 authors.

Ruben Ruiz-Mateos SerranoInstitute for Biomedical Innovation, University of Cambridge, Cambridge, UK.ORCID http://orcid.org/0000-0002-8501-7068
Charlie BruntInstitute for Biomedical Innovation, University of Cambridge, Cambridge, UK.
Xudong TaoInstitute for Biomedical Innovation, University of Cambridge, Cambridge, UK.ORCID http://orcid.org/0000-0001-8177-8831
Maciej ZajaczkowskiDepartment of Bioengineering, Faculty of Engineering, Imperial College London, London, UK.ORCID http://orcid.org/0000-0002-5883-9306
Antonio Dominguez-AlfaroElectrical Engineering Division, Department of Engineering, University of Cambridge, Cambridge, UK.
Matias L PicchioIKERBASQUE, Basque Foundation for Science, Bilbao, Spain.ORCID http://orcid.org/0000-0003-3454-5992
Daniele MantionePOLYMAT, University of the Basque Country UPV/EHU, Av.Tolosa 72, 20018, Donostia-San Sebastian, Gipuzkoa, Spain.ORCID http://orcid.org/0000-0001-5495-9856
Emmanuel M DrakakisDepartment of Bioengineering, Faculty of Engineering, Imperial College London, London, UK.
David MecerreyesPOLYMAT, University of the Basque Country UPV/EHU, Av.Tolosa 72, 20018, Donostia-San Sebastian, Gipuzkoa, Spain.
George G MalliarasInstitute for Biomedical Innovation, University of Cambridge, Cambridge, UK. gm603@cam.ac.uk.ORCID http://orcid.org/0000-0002-4582-8501

Funding

Eusko Jaurlaritza (Basque Government) IT1766-22Ikerbasque, Basque Foundation for Science RYC2024-048187-IRCUK | Engineering and Physical Sciences Research Council (EPSRC) EP/S022139/1
6 · The paper itself

Abstract

Cutaneous electrophysiology is a fundamental non-invasive technique for assessing electrically active organs such as the brain, heart, and muscles. Standard approaches, however, are limited in spatial resolution, reducing sensitivity to certain pathological features. The development of body surface potential mapping using electrode arrays has helped overcome these limitations, enhancing the diagnostic power of cutaneous recordings, yet clinical adoption remains constrained by challenges in electrode performance, wiring complexity, wearability, data transmission, and interpretability. Here, we present a hybrid e-textile electrode array system that overcomes these barriers, enabling simultaneous mapping of electrical activity along the cortico-muscular axis. The system combines application-specific conducting polymer coatings to improve electrode performance, a flexible fabrication process for robust connectivity and wearability, and interpretable machine learning algorithms for data analysis. In controlled single-subject experiments, we demonstrate reliable muscle and brain recordings, enabling classification of grasped object shapes and somatosensory stimuli. Simultaneous multi-site recordings along the cortico-muscular axis provide spatial maps of reaction time distributions and allow prediction of muscle activation patterns from cortical activity. This platform establishes a framework for wearable, multi-modal electrophysiological mapping and non-invasive study of cortico-muscular dynamics, representing a step towards practical brain-body interfaces with applications in neurorehabilitation, prosthetics, and human-machine interaction.

Indexed as

Body Surface Potential MappingMuscle, SkeletalTextilesAlgorithmsElectrodesHumansMachine LearningWearable Electronic Devices

Identifiers

PMID42420293
PMCPMC13478180

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.