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Concurrent control of natural and robotic limbs through a tactile-encoded brain-computer interface.

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Paper

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The authors' code

MATLAB · 13 lines · 455 B · no license

  1. function [data,chanlocsnew,srate] = EEGpreprocess(data,chanlocs)
  2. EEG = pop_importdata('data',data,'srate',1000,'chanlocs',chanlocs);
  3. EEG = pop_eegfiltnew(EEG,'locutoff',48,'hicutoff',52,'revfilt',1);
  4. EEG = pop_eegfiltnew(EEG,'locutoff',1,'hicutoff',10);
  5. EEG = pop_reref( EEG, {'M1' 'M2'});
  6. EEG = eeg_checkset(EEG);
  7. EEG = pop_rmbase(EEG,[]);
  8. EEG = pop_resample(EEG,100);
  9. chanlocsnew = EEG.chanlocs;
  10. srate = EEG.srate;
  11. data = EEG.data;
  12. clc
  13. end

EEGpreprocess.m at commit 913eda9, no license · at the source

Overview

Authors: Tianyu Jia1,2, Xingchen Yang1,3, Ciaran McGeady1, Yifeng Li1, Jinzhi Lin4, Kit San Ho2, Feiyu Pan2, Linhong Ji2, Chong Li4, Dario Farina1
ORCID iDs: Tianyu Jia, Xingchen Yang, Yifeng Li, Jinzhi Lin, Chong Li, Dario Farina
  1. Department of Bioengineering, Imperial College London, London, UK
  2. Department of Mechanical Engineering, Tsinghua University, Beijing, China
  3. School of Automation, Southeast University, Nanjing, China
  4. School of Biomedical Engineering, Tsinghua University, Beijing, China
Institutions: Imperial College London (United Kingdom); Tsinghua University (China); Southeast University (China)
Journal: Nature communications, volume 17, issue 1, article 8229
Dates: received 16 January 2026; accepted 19 June 2026; published online 2 July 2026
Type: Research article · Language: English
License: CC BY
Identifiers: DOI 10.1038/s41467-026-75213-3 · PMID 42393084 · PMCID PMC13462973 · OpenAlex W7167047749
Open access: gold, a free copy (OpenAlex)
Status: code verified
Categories: EEG (modality), human (organism), cognitive (subfield)
Methods: Spectral & time-frequency, Preprocessing, Connectivity, Statistics, Evoked potentials, Machine learning, Physiology & signal measures
Keywords: Biotechnology, Biological techniques, Neuroscience, Biomedical engineering
MeSH: Brain-Computer Interfaces*, Robotics*, Touch*, Adult, Dual-Task Tests, Electroencephalography, Event-Related Potentials, P300, Female, Humans, Male, Movement, Young Adult (* major topic)
Topic: EEG and Brain-Computer Interfaces (Cognitive Neuroscience, Neuroscience), according to OpenAlex
Funding: Government of the United Kingdom; UK Research and Innovation (10052152); Imperial College London; HORIZON EUROPE Framework Programme
Citations: not cited yet (Europe PMC); 48 references in the paper

Abstract

Brain-computer interfaces (BCIs) promise to extend human movement capabilities by enabling direct neural control of supernumerary effectors, yet integrating augmented commands with multiple degrees of freedom without disrupting natural movement remains a key challenge. Here, we propose a tactile-encoded BCI that leverages sensory afferents through a tactile-evoked P300 paradigm, allowing reliable decoding of supernumerary motor intentions even when superimposed with voluntary actions. The interface was evaluated in a multi-day experiment comprising a single motor recognition task to validate baseline BCI performance and a dual-task paradigm to assess the potential influence between the BCI and natural human movement. The interface achieved real-time and reliable decoding of four supernumerary degrees of freedom, with significant performance improvements after three days of training. After training, performance did not differ significantly between the single-task and dual-task conditions, and natural movement remained unimpaired during concurrent supernumerary control. Lastly, the interface was deployed in a movement augmentation task, demonstrating its ability to command two supernumerary robotic arms for functional assistance during bimanual tasks. These results establish a neural interface paradigm for movement augmentation through stimulation of sensory afferents, expanding motor degrees of freedom without impairing natural movement.

Reproduced under the paper's license (CC BY), from the paper cited above.

Repository

Its files are read in the Code ↔ Paper reader above.

jty940529/Tactile_P300_BCI

License: none: the authors keep all their rights
State: the link answers, verified on 27 September 2026
Evidence: files inventoried
Commit: 913eda974faa16ab78c81e498004ce7ca00c218c, 31 May 2026
Languages: MATLAB (3)
Size: 4 files, 3 scripts
Software Heritage: not archived
Found in: “Code availability”
Holds: README
Not found: license file, CITATION.cff, environment file, tests, continuous integration, documentation
Tools: EEGLAB (1 file)
Availability: 1 check, the latest on 27 September 2026: the link answers
  • 27 September 2026: the link answers
4 files
At the source: github.com/jty940529/Tactile_P300_BCI

Code availability

The code for online EEG pre-processing, decoding as well as P300 signal plotting used in this study is available on GitHub at: https://github.com/jty940529/Tactile_P300_BCI.

Reproduced under the paper's license (CC BY), from the paper cited above.

Tracing map

Proposed by the machine: these links were found in the paper and verified at the source, without human review. The map will receive a Zenodo DOI once one of the paper's authors has validated it with their ORCID.

What the map holds:

  • 1 repository of the authors' code, each at its verified commit, with its license and how the link was found in the paper;
  • 3 scripts, each with its path and the digest of its content;
  • no match between paragraphs and code yet;
  • neither the text of the paper nor the code itself.

Its JSON (tracing-map.json) is deposited on Zenodo with its DOI once the map is validated.

Data

Datasets cited

Data availability

All data supporting the findings of this study are available within the article and its supplementary files. Any additional requests for information can be directed to, and will be fulfilled by, the corresponding authors. The data for this study are publicly available at 10.5281/zenodo.17306307. Source data are provided with this paper.

Reproduced under the paper's license (CC BY), from the paper cited above.

Versions

The history of this record: each version stored by the harvester or made by a correction of its authors or of the maintainers of its code, and what changed in its facts. The texts of the paper (its abstract, its availability statements) are not part of it; versions that changed only those are not listed.

Version 2, 28 September 2026

  • Funding: added Government of the United Kingdom; UK Research and Innovation: 10052152; Imperial College London; HORIZON EUROPE Framework Programme

Version 1, 27 September 2026: the first record

Recorded: type, language, journal, volume, issue, pages, dates, 10 authors, 4 keywords, 12 MeSH terms, 41 references.

Cite

This paper

Jia, T., Yang, X., McGeady, C., Li, Y., Lin, J., Ho, K. S., Pan, F., Ji, L., Li, C., & Farina, D. (2026). Concurrent control of natural and robotic limbs through a tactile-encoded brain-computer interface. Nature communications, 17(1), 8229. https://doi.org/10.1038/s41467-026-75213-3

BibTeX

@article{jia2026concurrent,
author = {Jia, Tianyu and Yang, Xingchen and McGeady, Ciaran and Li, Yifeng and Lin, Jinzhi and Ho, Kit San and Pan, Feiyu and Ji, Linhong and Li, Chong and Farina, Dario},
title = {{Concurrent control of natural and robotic limbs through a tactile-encoded brain-computer interface}},
journal = {Nature communications},
year = {2026},
month = jul,
volume = {17},
number = {1},
pages = {8229},
publisher = {Nature Publishing Group},
issn = {2041-1723},
doi = {10.1038/s41467-026-75213-3},
url = {https://doi.org/10.1038/s41467-026-75213-3},
pmid = {42393084},
pmcid = {PMC13462973}
}

RIS

TY - JOUR
AU - Jia, Tianyu
AU - Yang, Xingchen
AU - McGeady, Ciaran
AU - Li, Yifeng
AU - Lin, Jinzhi
AU - Ho, Kit San
AU - Pan, Feiyu
AU - Ji, Linhong
AU - Li, Chong
AU - Farina, Dario
TI - Concurrent control of natural and robotic limbs through a tactile-encoded brain-computer interface
T2 - Nature communications
J2 - Nat Commun
PY - 2026
DA - 2026/07/02
VL - 17
IS - 1
SP - 8229
SN - 2041-1723
PB - Nature Publishing Group
DO - 10.1038/s41467-026-75213-3
UR - https://doi.org/10.1038/s41467-026-75213-3
LA - en
ER -

CSL-JSON

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"id": "10.1038/s41467-026-75213-3",
"type": "article-journal",
"title": "Concurrent control of natural and robotic limbs through a tactile-encoded brain-computer interface",
"container-title": "Nature communications",
"author": [
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"family": "Jia",
"given": "Tianyu"
},
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"family": "Yang",
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{
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"family": "Li",
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"family": "Lin",
"given": "Jinzhi"
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{
"family": "Ho",
"given": "Kit San"
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{
"family": "Pan",
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"family": "Ji",
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},
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"family": "Li",
"given": "Chong"
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],
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"issue": "1",
"page": "8229",
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"PMID": "42393084",
"PMCID": "PMC13462973",
"ISSN": "2041-1723",
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