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Advances on EEG-Based Sensing and Imaging: 2nd Edition
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Advances on EEG-Based Sensing and Imaging: 2nd Edition

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

Deadline for manuscript submissions: closed (20 October 2024) | Viewed by 4166

Special Issue Editors

Dr. Winko W. An

E-Mail Website
Guest Editor
Translational Neuroscience Center, Boston Children's Hospital, Harvard Medical School, Boston, MA 02115, USA
Interests: neurodevelopmental disorder; neuroimaging; biomedical signal processing; machine learning; brain–computer interface
Special Issues, Collections and Topics in MDPI journals
Dr. Laurel Gabard-Durnam

E-Mail Website
Guest Editor
Department of Psychology, College of Science, Northeastern University, Boston, MA 02115, USA
Interests: neuroplasticity; sensitive periods; EEG; fMRI; neuroimaging
Special Issues, Collections and Topics in MDPI journals
Dr. Wanze Xie

E-Mail Website
Guest Editor
School of Psychological and Cognitive Sciences, IDG/McGovern Institute for Brain Research, Peking University, Beijing 100871, China
Interests: child behaviors; ECG and EEG/ERP; cortical source localization; fNIRS and MRI neuroimaging techniques
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Following the success of the previous Special Issue "Advances on EEG-Based Sensing and Imaging" (https://www.mdpi.com/journal/sensors/special_issues/EEG_SI), we are pleased to announce the next in the series, entitled “Advances on EEG-Based Sensing and Imaging: 2nd Edition”.

In recent decades, electroencephalography (EEG) has received an increasing voume of attention from the neuroscience and neuroengineering community as a tool for a wide range of research, such as cognitive and behavioral neuroscience, psychology and psychiatry, biomarker discovery, and the brain–computer interface. This Special Issue of Sensors aims to communicate recent advances in the sensing techniques and analytical methods applied in EEG. Authors are invited to submit cutting-edge research on topics including, but not limited to, the following:

  • Development of EEG sensors and wearable devices, especially for brain–computer interfaces;
  • Multi-modal sensor fusion (e.g., EEG with fNIRS, fMRI, ECG, eye-tracking, etc.);
  • Application of signal processing techniques in EEG denoising, especially for data collected during motion and transportation, or from populations with a known characteristic of high noise level (e.g., infants and children);
  • Discovery of biomarkers in neurological and neurodevelopmental disorders;
  • Adoption of machine learning and deep learning algorithms in understanding large-scale EEG data.

Dr. Winko W. An
Dr. Laurel Gabard-Durnam
Dr. Wanze Xie
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 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

  • EEG
  • brain–computer interface
  • sensor fusion
  • denoising
  • neural biomarkers
  • machine learning
  • deep learning

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

Published Papers (3 papers)

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Research

14 pages, 17074 KiB  
Article
Enhancing Deep Sleep Induction Through a Wireless In-Ear EEG Device Delivering Binaural Beats and ASMR: A Proof-of-Concept Study
by Elke Hestermann, Kristiaan Schreve and David Vandenheever
Sensors 2024, 24(23), 7471; https://doi.org/10.3390/s24237471 - 22 Nov 2024
Abstract
This study presents the development of a wireless in-ear EEG device designed to monitor brain activity during sleep and deliver auditory stimuli aimed at enhancing deep sleep. The device records EEG signals and plays a combined auditory stimulus consisting of autonomous sensory meridian [...] Read more.
This study presents the development of a wireless in-ear EEG device designed to monitor brain activity during sleep and deliver auditory stimuli aimed at enhancing deep sleep. The device records EEG signals and plays a combined auditory stimulus consisting of autonomous sensory meridian response (ASMR) and 3 Hz binaural beats at a 60:30 dB ratio, intended to promote delta wave activity and non-rapid eye movement (NREM) stage 3 sleep. Fifteen participants completed this study, which included two consecutive nights: a baseline night and a testing night. Participants were divided into an experimental group, which received the combined ASMR and binaural beat stimulus, and a control group, which received only ASMR. The combined stimulus was delivered upon entering NREM stage 2 and replaced by ASMR when NREM stage 3 was reached. Results showed that the experimental group experienced an increase in NREM 3 sleep, a decrease in NREM 2 sleep, and a slight increase in NREM 3 latency compared to the baseline night. Although the findings are promising, further testing with a larger sample size is required to confirm the device’s potential to enhance sleep quality and promote delta activity in the brain. Full article
(This article belongs to the Special Issue Advances on EEG-Based Sensing and Imaging: 2nd Edition)
13 pages, 6513 KiB  
Article
A Phosphenotron Device for Sensoric Spatial Resolution of Phosphenes within the Visual Field Using Non-Invasive Transcranial Alternating Current Stimulation
by Faraz Sadrzadeh-Afsharazar and Alexandre Douplik
Sensors 2024, 24(8), 2512; https://doi.org/10.3390/s24082512 - 14 Apr 2024
Viewed by 2471
Abstract
This study presents phosphenotron, a device for enhancing the sensory spatial resolution of phosphenes in the visual field (VF). The phosphenotron employs a non-invasive transcranial alternating current stimulation (NITACS) to modulate brain activity by applying weak electrical currents to the scalp or face. [...] Read more.
This study presents phosphenotron, a device for enhancing the sensory spatial resolution of phosphenes in the visual field (VF). The phosphenotron employs a non-invasive transcranial alternating current stimulation (NITACS) to modulate brain activity by applying weak electrical currents to the scalp or face. NITACS’s unique application induces phosphenes, a phenomenon where light is perceived without external stimuli. Unlike previous invasive methods, NITACS offers a non-invasive approach to create these effects. The study focused on assessing the spatial resolution of NITACS-induced phosphenes, crucial for advancements in visual aid technology and neuroscience. Eight participants were subjected to NITACS using a novel electrode arrangement around the eye orbits. Results showed that NITACS could generate spatially defined phosphene patterns in the VF, varying among individuals but consistently appearing within their VF and remaining stable through multiple stimulations. The study established optimal parameters for vibrant phosphene induction without discomfort and identified electrode positions that altered phosphene locations within different VF regions. Receiver Operating characteristics analysis indicated a specificity of 70.7%, sensitivity of 73.9%, and a control trial accuracy of 98.4%. These findings suggest that NITACS is a promising, reliable method for non-invasive visual perception modulation through phosphene generation. Full article
(This article belongs to the Special Issue Advances on EEG-Based Sensing and Imaging: 2nd Edition)
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18 pages, 1259 KiB  
Article
Neurophysiological and Autonomic Correlates of Metacognitive Control of and Resistance to Distractors in Ecological Setting: A Pilot Study
by Michela Balconi, Carlotta Acconito, Roberta A. Allegretta and Laura Angioletti
Sensors 2024, 24(7), 2171; https://doi.org/10.3390/s24072171 - 28 Mar 2024
Viewed by 918
Abstract
In organisational contexts, professionals are required to decide dynamically and prioritise unexpected external inputs deriving from multiple sources. In the present study, we applied a multimethodological neuroscientific approach to investigate the ability to resist and control ecological distractors during decision-making and to explore [...] Read more.
In organisational contexts, professionals are required to decide dynamically and prioritise unexpected external inputs deriving from multiple sources. In the present study, we applied a multimethodological neuroscientific approach to investigate the ability to resist and control ecological distractors during decision-making and to explore whether a specific behavioural, neurophysiological (i.e., delta, theta, alpha and beta EEG band), or autonomic (i.e., heart rate—HR, and skin conductance response—SCR) pattern is correlated with specific personality profiles, collected with the 10-item Big Five Inventory. Twenty-four participants performed a novel Resistance to Ecological Distractors (RED) task aimed at exploring the ability to resist and control distractors and the level of coherence and awareness of behaviour (metacognition ability), while neurophysiological and autonomic measures were collected. The behavioural results highlighted that effectiveness in performance did not require self-control and metacognition behaviour and that being proficient in metacognition can have an impact on performance. Moreover, it was shown that the ability to resist ecological distractors is related to a specific autonomic profile (HR and SCR decrease) and that the neurophysiological and autonomic activations during task execution correlate with specific personality profiles. The agreeableness profile was negatively correlated with the EEG theta band and positively with the EEG beta band, the conscientiousness profile was negatively correlated with the EEG alpha band, and the extroversion profile was positively correlated with the EEG beta band. Taken together, these findings describe and disentangle the hidden relationship that lies beneath individuals’ decision to inhibit or activate intentionally a specific behaviour, such as responding, or not, to an external stimulus, in ecological conditions. Full article
(This article belongs to the Special Issue Advances on EEG-Based Sensing and Imaging: 2nd Edition)
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