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Latest Developments in Biopotential Sensor Development for Brain Signals
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Latest Developments in Biopotential Sensor Development for Brain Signals

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

Deadline for manuscript submissions: 30 April 2026 | Viewed by 718

Special Issue Editor

Prof. Dr. Walter Besio

E-Mail Website
Guest Editor
Department of Electrical, Computer and Biomedical Engineering, University of Rhode Island, Kingston, RI 02881, USA
Interests: electrodes; epilepsy; bi-directional brain computer interfacing

Special Issue Information

Dear Colleagues,

Biopotential sensors, specifically electrodes, play a crucial role in diagnosis, neuroscience, and medical research. These sensors are essential for accurately detecting and measuring electrical signals generated by biological tissues, particularly the brain. Over the past few years, the development of biopotential sensors, encompassing both invasive and noninvasive technologies, has seen significant advancements. This progress has opened new avenues for research and clinical applications.

This Special Issue is dedicated to exploring the latest advancements in the development and application of biopotential sensors for acquiring brain signals. It aims to highlight innovative sensors and methodologies that enhance the precision and reliability of brain signal acquisition. Additionally, this issue will welcome contributions that introduce novel techniques for analyzing brain biopotential signals, as well as practical applications of these technologies.

One of the exciting frontiers in this field is the integration of artificial intelligence with brain biopotential signals. This combination holds the potential to uncover new biomarkers for diagnosing brain diseases and disorders. Furthermore, it can significantly advance the field of brain–computer interfacing, enabling more effective communication and control systems for individuals with neurological conditions. By fostering interdisciplinary collaboration and innovation, this Special Issue aspires to push the boundaries of what is possible in neuroscience and medical research.

Prof. Dr. Walter Besio
Guest Editor

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 100 words) can be sent to the Editorial Office for announcement on this website.

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

  • biopotential sensors
  • electrodes
  • brain signals
  • brain–computer interface

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Published Papers (1 paper)

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Research

18 pages, 2062 KiB  
Article
Measuring Blink-Related Brainwaves Using Low-Density Electroencephalography with Textile Electrodes for Real-World Applications
by Emily Acampora, Sujoy Ghosh Hajra and Careesa Chang Liu
Sensors 2025, 25(14), 4486; https://doi.org/10.3390/s25144486 - 18 Jul 2025
Viewed by 260
Abstract
Background: Electroencephalography (EEG) systems based on textile electrodes are increasingly being developed to address the need for more wearable sensor systems for brain function monitoring. Blink-related oscillations (BROs) are a new measure of brain function that corresponds to brainwave responses occurring after [...] Read more.
Background: Electroencephalography (EEG) systems based on textile electrodes are increasingly being developed to address the need for more wearable sensor systems for brain function monitoring. Blink-related oscillations (BROs) are a new measure of brain function that corresponds to brainwave responses occurring after spontaneous blinking, and indexes neural processes as the brain evaluates new visual information appearing after eye re-opening. Prior studies have reported BRO utility as both a clinical and non-clinical biomarker of cognition, but no study has demonstrated BRO measurement using textile-based EEG devices that facilitate user comfort for real-world applications. Methods: We investigated BRO measurement using a four-channel EEG system with textile electrodes by extracting BRO responses using existing, publicly available EEG data (n = 9). We compared BRO effects derived from textile-based electrodes with those from standard dry Ag/Ag-Cl electrodes collected at the same locations (i.e., Fp1, Fp2, F7, F8) and using the same EEG amplifier. Results: Results showed that BRO effects measured using textile electrodes exhibited similar features in both time and frequency domains compared to dry Ag/Ag-Cl electrodes. Data from both technologies also showed similar performance in artifact removal and signal capture. Conclusions: These findings provide the first demonstration of successful BRO signal capture using four-channel EEG with textile electrodes, providing compelling evidence toward the development of a comfortable and user-friendly EEG technology that uses the simple activity of blinking for objective brain function assessment in a variety of settings. Full article
(This article belongs to the Special Issue Latest Developments in Biopotential Sensor Development for Brain Signals)
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