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Advances in EEG Sensors: Research and Applications

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

Deadline for manuscript submissions: 20 December 2025 | Viewed by 638

Special Issue Editor


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Guest Editor
Laboratory of Solid State Optoelectronics Information Technology, Institute of Semiconductors, Chinese Academy of Sciences, Beijing 100083, China
Interests: neural interface device and technology; EEG electrode implantable electrode

Special Issue Information

Dear Colleagues,

In recent years, research on the semantic analysis and understanding of brain signals using biological signals and their application to BCI has been widely conducted. The acquisition of brain signals involves signals obtained from various devices and machines, such as EEG, NIRS, fMRI, and MEG devices. Here, noise in signals is an issue.

Technological advances in EEG sensors and electronics (e.g., dry electrodes and miniaturized amplifiers) have made EEG systems easy-to-mount and sufficiently lightweight to enable continuous, accurate, and mobile recordings. Hardware portability, reduced preparation times, high spatial resolution, consistently stable and high-quality signal over prolonged use, good comfort levels, and the wireless transmission of EEG signals are all requirements of neuroscience investigations in ecological conditions. With this in mind, the forthcoming Special Issue aims to solicit articles from academic and industrial institutions with original contributions on advances in EEG sensors that could be beneficial for biomedical applications, basic neuroscience, and clinical investigations from neonates to adults.

The Special Issue welcomes contributions from the academic community in the following areas:

  • Biological signal acquisition and processing;
  • Electrode designs (biopotential electrodes, EEG electrodes, dry electrodes and semidry electrodes);
  • Brain–computer interfaces and neuro-interfaces for rehabilitation and assistive technologies;
  • Wireless and wearable EEG systems for real-time monitoring;
  • Machine learning and AI-driven EEG signal processing;
  • Applications in epilepsy, Alzheimer’s, Parkinson’s, and mental health diagnostics;
  • Low-power and portable EEG devices for point-of-care.

Prof. Dr. Weihua Pei
Guest Editor

Manuscript Submission Information

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Keywords

  • EEG sensors
  • biological signals
  • EEG electrodes

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Published Papers (1 paper)

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Research

15 pages, 3209 KB  
Article
The Impact of Chinese Martial Arts Sanda Training on Cognitive Control and ERP: An EEG Sensors Study
by Yanan Li, Haojie Li and Haidong Jiang
Sensors 2025, 25(19), 5996; https://doi.org/10.3390/s25195996 - 29 Sep 2025
Viewed by 447
Abstract
Objective: This study aimed to explore the impact of sanda sports experience on cognitive control using electroencephalography (EEG). Methods: The study involved 38 male participants, including 19 sanda athletes with over 5 years of training and 19 ordinary college students. A 2 × [...] Read more.
Objective: This study aimed to explore the impact of sanda sports experience on cognitive control using electroencephalography (EEG). Methods: The study involved 38 male participants, including 19 sanda athletes with over 5 years of training and 19 ordinary college students. A 2 × 4 mixed experimental design was used, with group (sanda athletes vs. ordinary college students) as the between-subjects variable and four experimental conditions (consistent in the previous and current trials, consistent in the previous but inconsistent in the current trials, inconsistent in the previous but consistent in the current trials, and inconsistent in both previous and current trials) as the within-subjects variable. The classic color-word Stroop task was employed to measure cognitive control function through reaction time, accuracy, and event-related potential (ERP) amplitude. Results: Sanda athletes exhibited significantly shorter reaction times than ordinary college students across all conditions (p < 0.05). There was no significant difference in accuracy between the two groups (p > 0.05). ERP results showed that sanda athletes had significantly larger amplitudes for the N200 and P300 components in incongruent trials compared to congruent trials (p < 0.05), and significantly larger N400 amplitudes in incongruent trials than ordinary college students (p < 0.05). Conclusions: Sanda athletes demonstrated faster response speed and enhanced cognitive control abilities, as indicated by ERP components, without sacrificing task accuracy. Full article
(This article belongs to the Special Issue Advances in EEG Sensors: Research and Applications)
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