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An Arduino-Based, Portable Prototype for the Recording and Analysis of EEG Signals to Support Self-Detection and Self-Monitoring of Stress.

Overview

Authors: Stamatios Baltzis1, Gerasimos Pagiatakis1, Nikolaos Voudoukis2, Andreas Papadakis1, Leonidas Dritsas1, Dimitris Uzunidis3
ORCID iDs: Gerasimos Pagiatakis, Nikolaos Voudoukis, Andreas Papadakis, Leonidas Dritsas, Dimitris Uzunidis
  1. Department of Electrical & Electronic Engineering Educators, School of Pedagogical and Technological Education, 15122 Maroussi, Attica, Greece; (S.B.); (G.P.); (A.P.); (L.D.)
  2. Department of Electrical & Computer Engineering, National Technical University of Athens, 15772 Athens, Attica, Greece
  3. National Center of Scientific Research “Demokritos”, 15341 Athens, Attica, Greece
Institutions: School of Pedagogical and Technological Education (Greece); National Technical University of Athens (Greece); National Centre of Scientific Research "Demokritos" (Greece)
Journal: Sensors (Basel, Switzerland), volume 26, issue 11, article 3410
Dates: received 12 March 2026; accepted 25 May 2026; published online 28 May 2026
Type: Research article · Language: English
License: CC BY
Identifiers: DOI 10.3390/s26113410 · PMID 42280930 · PMCID PMC13259060 · OpenAlex W7162672271
Open access: gold, a free copy (OpenAlex)
Status: data only
Categories: EEG (modality), human (organism), methods / tools (subfield)
Methods: Spectral & time-frequency, Preprocessing, Machine learning, Statistics, Physiology & signal measures
Keywords: electroencephalogram, brain signals, alpha signal, beta signal, stress, Arduino
MeSH: Electroencephalography*, Signal Processing, Computer-Assisted*, Stress, Psychological*, Equipment Design, Humans, Software (* major topic)
Topic: Emotion and Mood Recognition (Experimental and Cognitive Psychology, Psychology), according to OpenAlex
Citations: not cited yet (Europe PMC); 29 references in the paper
Research resources: RRID:SCR_007345

Abstract

This article describes a portable Arduino-based prototype for the recording and analysis of electroencephalogram (EEG) signals associated with anxiety situations. The system’s main aim is to enable the user to self-detect stress and take self-regulating/relaxing actions in real time before stress escalates. The recorded EEG signals are first processed in the analog domain (including amplification and noise reduction) and then, by using an Arduino Uno board, they are converted into digital format and transmitted through either a wired or wireless connection to a computer to be depicted in both the time and the frequency domains by means of an open-source software. During the performed tests, the system successfully showed visible changes in the alpha and beta brain signals corresponding to the states of resting, induced stress, and the subsequent self-regulation/relaxation process. The proposed prototype (though non-clinical in its present form) has the merits of relatively low cost, easy self-use (outside clinical environments), and real-time EEG signal depiction, and, apart from enabling the user to self-detect and self-monitor stress, it can also be used for educational and/or research purposes.

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

Code

The paper links to its data, not to its authors' code: see the Data section.

Tracing map

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Data

Datasets cited

Data Availability Statement

The original contributions presented in this study are included in the article. Further inquiries can be directed to the corresponding author.

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 1, 28 September 2026: the first record

Recorded: type, language, journal, volume, issue, pages, dates, 6 authors, 6 keywords, 6 MeSH terms, 15 references, 1 RRID.

Cite

This paper

Baltzis, S., Pagiatakis, G., Voudoukis, N., Papadakis, A., Dritsas, L., & Uzunidis, D. (2026). An Arduino-Based, Portable Prototype for the Recording and Analysis of EEG Signals to Support Self-Detection and Self-Monitoring of Stress. Sensors (Basel, Switzerland), 26(11), 3410. https://doi.org/10.3390/s26113410

BibTeX

@article{baltzis2026arduino,
author = {Baltzis, Stamatios and Pagiatakis, Gerasimos and Voudoukis, Nikolaos and Papadakis, Andreas and Dritsas, Leonidas and Uzunidis, Dimitris},
title = {{An Arduino-Based, Portable Prototype for the Recording and Analysis of EEG Signals to Support Self-Detection and Self-Monitoring of Stress}},
journal = {Sensors (Basel, Switzerland)},
year = {2026},
month = may,
volume = {26},
number = {11},
pages = {3410},
publisher = {Multidisciplinary Digital Publishing Institute (MDPI)},
issn = {1424-8220},
doi = {10.3390/s26113410},
url = {https://doi.org/10.3390/s26113410},
pmid = {42280930},
pmcid = {PMC13259060}
}

RIS

TY - JOUR
AU - Baltzis, Stamatios
AU - Pagiatakis, Gerasimos
AU - Voudoukis, Nikolaos
AU - Papadakis, Andreas
AU - Dritsas, Leonidas
AU - Uzunidis, Dimitris
TI - An Arduino-Based, Portable Prototype for the Recording and Analysis of EEG Signals to Support Self-Detection and Self-Monitoring of Stress
T2 - Sensors (Basel, Switzerland)
J2 - Sensors (Basel)
PY - 2026
DA - 2026/05/28
VL - 26
IS - 11
SP - 3410
SN - 1424-8220
PB - Multidisciplinary Digital Publishing Institute (MDPI)
DO - 10.3390/s26113410
UR - https://doi.org/10.3390/s26113410
LA - en
ER -

CSL-JSON

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