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Advances in Wearable Electroencephalography Sensor Technology

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Wearables".

Deadline for manuscript submissions: 30 September 2026 | Viewed by 1601

Special Issue Editors


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Guest Editor
Department of Mathematics, Informatics and Geosciences, University of Trieste, Piazzale Europa, 1, 34127 Trieste, Italy
Interests: computational neuroscience; time-series; data quality; machine learning; AI; EEG; brain-computer interface; BCI
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
Department of Information Engineering, University of Padova, Via Gradenigo 6B, 35131 Padova, Italy
Interests: radiation effects in CMOS transistors; total ionizing dose in electronics; reliability of devices; nanometer-scale semiconductor technologies; electrochemical sensors; capacitive sensors; biodevices
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Electroencephalography (EEG) has long been a cornerstone of neurophysiological monitoring and brain–computer interface (BCI) systems. With the rise of wearable technologies and the demand for continuous real-world monitoring, wearable EEG sensors are undergoing rapid innovation. Advances in materials science, electronics, signal processing, and AI are enabling the development of more compact, comfortable, and high-resolution EEG systems suitable for ambulatory use across healthcare, neuroscience, cognitive research, and consumer applications.

This Special Issue aims to gather original research and review articles that address the latest developments, breakthroughs, and challenges in wearable EEG sensor technologies. We particularly welcome contributions exploring novel sensor designs, EEG integration with wireless platforms, energy-efficient signal acquisition, artifact reduction, real-time analysis, and diverse applications in clinical and non-clinical settings. We especially encourage submissions focused on the development of non-obtrusive, user-friendly, and ecologically valid EEG devices designed for non-expert populations, such as elderly individuals, to support widespread and inclusive adoption.

Topics of interest include, but are not limited to, the following:

  • Flexible, dry, and textile-based EEG electrodes;
  • Ear-EEG;
  • Wireless and wearable EEG-based BCI systems;
  • Artifact removal and signal enhancement for mobile EEG;
  • EEG-based mental health and neurological monitoring;
  • Multi-modal sensor integration with EEG;
  • AI and edge computing for EEG data analysis;
  • Neurofeedback and cognitive state monitoring using wearable EEG;
  • EEG applications in sleep, emotion, and attention tracking;
  • Standardization, privacy, and ethics in wearable EEG.

We invite contributions that push the boundaries of wearable EEG technology and pave the way for future neurotechnological applications.

Dr. Giulia Cisotto
Dr. Stefano Bonaldo
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sensors is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • wearable EEG
  • neurological monitoring
  • brain-computer interface
  • real-time monitoring
  • sleep monitoring

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Published Papers (1 paper)

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Research

14 pages, 2129 KB  
Article
Carbon Nanotube Hydrogel Electrodes for High-Fidelity Intra-Aural EEG in Wearable Neurotechnology
by Alexandra-Ștefania Mihai, Ana-Maria Iordache, Liliana Vereștiuc, Isabella Nacu and Oana Geman
Sensors 2026, 26(10), 2973; https://doi.org/10.3390/s26102973 - 8 May 2026
Viewed by 962
Abstract
Electrical monitoring of brain activity can be performed discreetly and continuously over long periods of time using intra-auricular electroencephalography (intra-auricular EEG), a promising technique suitable for subjects who are difficult to monitor, such as newborns or patients with neurological conditions requiring discreet but [...] Read more.
Electrical monitoring of brain activity can be performed discreetly and continuously over long periods of time using intra-auricular electroencephalography (intra-auricular EEG), a promising technique suitable for subjects who are difficult to monitor, such as newborns or patients with neurological conditions requiring discreet but long-term neurophysiological assessment. The concept of intra-aural EEG can be realized through the development of systems that include wearable sensors, whose performance critically depends on the development of biocompatible electrode materials that exhibit low impedance and can maintain and provide stable contact between the electrode and the epithelial tissue. Based on our previous work on carbon nanotube (CNT)-based hydrogel composites for intra-aural EEG electrodes, this study focuses on the electrochemical characterization of hydrogels initially prepared from gelatin methacrylate (GelMA)/2-hydroxyethyl methacrylate (HEMA) doped with varying concentrations of CNTs (0–3 wt%). In the present study, the materials obtained in the first stage were evaluated using electrochemical impedance spectroscopy (EIS) under both liquid and dry conditions, supplemented by measurements of hydration capacity. The results show that the composite with 3% CNT content exhibits suitable properties, making the material making the 3 wt% CNT formulation a promising platform for the further development of 3D-printable hydrogel electrodes for intra-aural EEG applications. Equivalent circuit modeling reveals improved ionic and electronic conductivity compared to the undoped hydrogel, attributed to better CNT dispersion and polymer crosslinking. This work provides insights into the structure–property relationships of CNT–hydrogel composites and lays the foundation for the further development of a 3D-printed and in vitro/in vivo validated prototype of intra-aural EEG sensors. Full article
(This article belongs to the Special Issue Advances in Wearable Electroencephalography Sensor Technology)
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