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An intelligent EEG-based ensemble framework for communication assistance in Locked-In Syndrome patients.

Overview

Authors: Arun Kumar Selvam1, Anand Loganathan2
  1. School of Computing, Department of Computer Science and Engineering, SRM Institute of Science and Technology,Potheri, SRM Nagar, Kattankulathur, Tamil Nadu India
  2. School of Computing, Department of Networking and Communications, SRM Institute of Science and Technology,Potheri, SRM Nagar, Kattankulathur, Tamil Nadu India
Institutions: SRM Institute of Science and Technology (India)
Journal: Scientific reports, volume 16, issue 1, article 18115
Dates: received 1 December 2025; accepted 29 March 2026; published online 19 April 2026
Type: Research article · Language: English
License: CC BY-NC-ND
Identifiers: DOI 10.1038/s41598-026-47041-4 · PMID 42002556 · PMCID PMC13254361 · OpenAlex W7154913985
Open access: gold, a free copy (OpenAlex)
Status: data only
Categories: EEG (modality), human (organism), other condition (population), clinical / translational (subfield)
Methods: Spectral & time-frequency, Preprocessing, Connectivity, Machine learning, Statistics, Evoked potentials
Keywords: Brain–computer interface, P300 speller, Electroencephalography, Ensemble learning, Amyotrophic lateral sclerosis, Locked-In Syndrome, Computational biology and bioinformatics, Engineering, Mathematics and computing, Neurology, Neuroscience
MeSH: Brain-Computer Interfaces*, Electroencephalography*, Locked-In Syndrome*, Adult, Communication, Communication Devices for People with Disabilities, Event-Related Potentials, P300, Female, Humans, Male, Random Forest, Support Vector Machine (* major topic)
Topic: EEG and Brain-Computer Interfaces (Cognitive Neuroscience, Neuroscience), according to OpenAlex
Citations: not cited yet (Europe PMC); 56 references in the paper

Abstract

The abstract is not reproduced here: the paper's license (CC BY-NC-ND) does not allow it. Read it in the paper, at the publisher or on Europe PMC.

Code

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The paper's code and data availability statement is in the Data section.

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Data

Datasets cited

Code and data availability statement

The paper has a code and data availability statement. Its license (CC BY-NC-ND) does not allow reproducing it here; in short, from what the harvester recognized in it:

Read it in the paper: doi.org/10.1038/s41598-026-47041-4.

Versions

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Version 1, 29 September 2026: the first record

Recorded: type, language, journal, volume, issue, pages, dates, 2 authors, 11 keywords, 12 MeSH terms, 22 references.

Cite

This paper

Selvam, A. K., & Loganathan, A. (2026). An intelligent EEG-based ensemble framework for communication assistance in Locked-In Syndrome patients. Scientific reports, 16(1), 18115. https://doi.org/10.1038/s41598-026-47041-4

BibTeX

@article{selvam2026intelligent,
author = {Selvam, Arun Kumar and Loganathan, Anand},
title = {{An intelligent EEG-based ensemble framework for communication assistance in Locked-In Syndrome patients}},
journal = {Scientific reports},
year = {2026},
month = apr,
volume = {16},
number = {1},
pages = {18115},
publisher = {Nature Publishing Group},
issn = {2045-2322},
doi = {10.1038/s41598-026-47041-4},
url = {https://doi.org/10.1038/s41598-026-47041-4},
pmid = {42002556},
pmcid = {PMC13254361}
}

RIS

TY - JOUR
AU - Selvam, Arun Kumar
AU - Loganathan, Anand
TI - An intelligent EEG-based ensemble framework for communication assistance in Locked-In Syndrome patients
T2 - Scientific reports
J2 - Sci Rep
PY - 2026
DA - 2026/04/19
VL - 16
IS - 1
SP - 18115
SN - 2045-2322
PB - Nature Publishing Group
DO - 10.1038/s41598-026-47041-4
UR - https://doi.org/10.1038/s41598-026-47041-4
LA - en
ER -

CSL-JSON

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