Electroencephalography 3.0: From the Laboratory to the Mass-Market for a Daily-Life Use
A special issue of Brain Sciences (ISSN 2076-3425). This special issue belongs to the section "Neurotechnology and Neuroimaging".
Deadline for manuscript submissions: closed (25 August 2023) | Viewed by 12928
Special Issue Editors
Interests: cognitive neuroscience; behavioural neuroscience; neuropsychology, biosignals processing; brain-computer interface; human-machine interaction; human factor; road safety
Special Issues, Collections and Topics in MDPI journals
Interests: applied artificial intelligence & machine learning; data analytics; statistical learning theory; signal processing and multi-sensor data fusion; distributed AI and ML for big data
Special Issue Information
Dear Colleagues,
Electroencephalography (EEG) is a well-established neuroimaging tool to record brain electrophysiological activity. Developed almost one century ago, it has been employed as the main non-invasive tool for investigating brain activity with regard to clinical pathologies, such as epilepsy, post-stroke injuries, sleep disorders and brain damages. Besides the mere medical purposes, EEG has been also one of the main research tools within the neuroscientific field, where brain activity is investigated in relation to human behavior. In the second half of twentieth century, EEG technique lived a sort of revolution when the first
Brain–Computer Interfaces (BCI) were theorized and developed. EEG was no longer just a technique for passively monitoring brain activity, but it was used as a new active channel of communication for controlling external devices and/or prosthetics: new applications were so developed for restoring, replacing and augmenting human capabilities. Anyhow, its use was still confined to medical and research laboratories.
During the last decade the EEG is living its “third revolution”: thanks to the recent technological progress in terms of materials and electronics, as well as the advancements in terms of signal processing, new wearable EEG devices have been developed to be employed outside the traditional research laboratories.
First low-cost EEG devices generated a large debate, since their signal quality and reliability were questionable. However, their potential impact in a huge set of daily-life applications, such as human factor assessment in critical environments, integration into in-vehicles safety systems, gaming, learning, and even e-healthy, appeared immediately clear and ground-braking.
The aim of the present special issue is to collect up to date research and works on new and innovative technologies and methods for EEG-based applications with healthy people and/or patients, with a specific focus on challenges and concerns related to “out-of-the-lab” context.
We are inviting original research work (research articles, narrative reviews, systematic reviews, meta-analyses, case studies) covering novel theories, innovative methods, advanced technologies, and meaningful applications that can potentially lead to significant advances in EEG research for a daily-life deployment
Dr. Gianluca Di Flumeri
Dr. Shaibal Barua
Guest Editors
Manuscript Submission Information
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Keywords
- electroencephalography
- neuroimaging
- neurotechnology
- wearable devices
- brain-computer interface
- machine learning
- neuroscience
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