[Eeglablist] Special Issue: "Advances in Principles, Methods and Applications of Brain-Computer Interaction"

[Athanasios Vourvopoulos]

*Title*: Advances in Principles, Methods and Applications of 
Brain-Computer Interaction*
*

*Website*: https://urldefense.com/v3/__https://www.mdpi.com/si/161595__;!!Mih3wA!F6WgVm4FSzo-oB9u9Z6_QC0gpLU07auICf8CWmJZ-Ca6I6DuM3EukNZvojwS9YMH5Zwbn8byUS00XDmustxzexkjN1tIpUQF2Ro6yDpIcA$ 

*Special Issue Information:*

Brain–computer interfaces (BCIs) represent a continuously growing 
research field that originated in an attempt to enable subjects with 
severe neuromuscular disorders to communicate and interact with the 
world around them. Advances in the capabilities of sensors, computation 
devices, and wireless technologies, as well as in signal processing, 
machine learning and neuroscience methods have expanded the BCI concept, 
and it is now subject to investigation in a wide range of fields such as 
remote healthcare, industry, marketing, education, and gaming. Recently, 
the use of BCI technology in other aspects of daily life, including 
mental load management, decision making, neuro-marketing, and gaming, 
has been explored. As the aspiration is that BCI technology will 
gradually move towards use in practical applications, the need for more 
reliable and robust solutions for detecting user intent is, in the 
current landscape, as urgent and important as it ever has been. The 
battle to deploy BCI technology in real-world settings is fought on 
multiple fronts. Novel neural interface and other hardware devices 
promise to improve the signal-to-noise rate of brain signals and user 
acceptance. Continued efforts in signal processing and artificial 
intelligence are enhancing the decoding capabilities of BCIs. New 
developments in the design principles of BCI systems, such as 
shared-control, hybrid BCI and co-adaptive user training are finding use 
in attempts to widen user access to BCI apparatuses. Additionally, 
increasing the user evaluation of established and novel BCI applications 
is broadening the scope of application and enriching the field with 
valuable end- and professional user feedback.

This Special Issue aims to collect papers on a broad spectrum of 
specific topics reflecting recent advances in the methodology, design 
and applicability of BCI. The following are indicative of the kind of 
topics under discussion:

  *      Low-cost, portable, unobtrusive and robust sensors for
    brain–computer interfaces;
  *      Open-source software platforms for BCI;
  *      The combination of brain imaging technologies with
    physiological sensors
  *      Brain–computer interface applications and user evaluation studies;
  *      Novel signal processing and machine learning for BCI, with
    emphasis on transfer and deep learning methods;
  *      New user training paradigms and advanced co-adaptive approaches
    for BCI learning;
  *      Benchmarking studies and production of big datasets BCI methods.


*Guest Editors:*

Dr. Serafeim Perdikis
Brain-Computer Interfaces and Neural Engineering Laboratory, School of 
Computer Science and Electronic Engineering, University of Essex, 
Colchester, UK

Dr. Athanasios Vourvopoulos
Institute for Systems and Robotics-Lisboa, Instituto Superior Técnico, 
Universidade de Lisboa, 1049-001 Lisbon, Portugal