sensors-logo

Journal Browser

Journal Browser

Advanced EEG Sensing and Brain–Computer Interfaces for Neuroengineering

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

Deadline for manuscript submissions: 30 June 2026 | Viewed by 399

Special Issue Editor


E-Mail Website
Guest Editor
Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin 300052, China
Interests: brain–computer interface; EEG; biosignal processing; neurophysiological monitoring

Special Issue Information

Dear Colleagues,

This Special Issue aims to highlight the latest advances in EEG sensing technologies and Brain–Computer Interfaces (BCIs) that are transforming the landscape of neuroengineering and human–machine symbiosis. As noninvasive neurotechnologies become more precise and accessible, novel developments in wearable EEG systems, dry and flexible electrodes, and AI-driven signal decoding are opening new possibilities for clinical neuroscience, rehabilitation, and cognitive augmentation.

We invite contributions that address breakthroughs in signal acquisition, noise reduction, feature extraction, connectivity analysis, and neuromodulation interfaces. Studies integrating machine learning, deep learning, and neurofeedback frameworks to enhance decoding performance are especially encouraged. The goal is to advance the design of smarter, adaptive, and interpretable BCI systems for both healthcare and everyday neurotechnology applications.

Dr. Yufeng Ke
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 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

  • electroencephalography (EEG)
  • brain–computer interface (BCI)
  • neuroengineering
  • biosignal processing
  • machine learning
  • wearable EEG
  • neural decoding
  • neurorehabilitation
  • noninvasive sensing
  • human–machine interaction

Benefits of Publishing in a Special Issue

  • Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
  • Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
  • Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
  • External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
  • Reprint: MDPI Books provides the opportunity to republish successful Special Issues in book format, both online and in print.

Further information on MDPI's Special Issue policies can be found here.

Published Papers (1 paper)

Order results
Result details
Select all
Export citation of selected articles as:

Research

12 pages, 1144 KB  
Article
Baseline Resting-State Network Integration Modulates Task Performance and Aftereffect
by Rok Požar, Tim Martin, Mary Katherine Kerlin, Aidan McColligan, Bruno Giordani and Voyko Kavcic
Sensors 2026, 26(1), 41; https://doi.org/10.3390/s26010041 - 20 Dec 2025
Viewed by 282
Abstract
Understanding how intrinsic brain networks adapt to cognitive demands is central to neuroscience. The aim of this study was to examine how eyes-open and eyes-closed resting-state network integration, derived from electroencephalography before and after a visual oddball task, relates to task performance in [...] Read more.
Understanding how intrinsic brain networks adapt to cognitive demands is central to neuroscience. The aim of this study was to examine how eyes-open and eyes-closed resting-state network integration, derived from electroencephalography before and after a visual oddball task, relates to task performance in young adults. Task engagement reduced global integration in theta, lower alpha, and beta bands, independent of eye condition, indicating a transient shift toward a less demanding post-task configuration. Eyes-open resting states consistently exhibited higher integration than eyes-closed in the upper alpha band, both before and after the task, reflecting enhanced inter-regional communication and sensory readiness. Importantly, higher pre-task beta-band integration during eyes-open resting state predicted faster reaction times and larger post-task decreases in integration, highlighting baseline network organization as a determinant of cognitive efficiency and neural flexibility. These findings support the concept of neural reserve, where intrinsic network efficiency and adaptability underpin both performance readiness and dynamic reorganization. Overall, the results demonstrate that resting-state network integration—modulated by both eye condition and task engagement—captures fundamental aspects of the brain’s capacity for efficient and flexible cognitive function. Full article
Show Figures

Figure 1

Back to TopTop