Current Status, Challenges, and Possible Solutions of EEG-Based Brain-Computer Interface: A Comprehensive Review

Abstract

Brain-Computer Interface (BCI), in essence, aims at controlling different assistive devices through the utilization of brain waves. It is worth noting that the application of BCI is not limited to medical applications, and hence, the research in this field has gained due attention. Moreover, the significant number of related publications over the past two decades further indicates the consistent improvements and breakthroughs that have been made in this particular field. Nonetheless, it is also worth mentioning that with these improvements, new challenges are constantly discovered. This article provides a comprehensive review of the state-of-the-art of a complete BCI system. First, a brief overview of electroencephalogram (EEG)-based BCI systems is given. Secondly, a considerable number of popular BCI applications are reviewed in terms of electrophysiological control signals, feature extraction, classification algorithms, and performance evaluation metrics. Finally, the challenges to the recent BCI systems are discussed, and possible solutions to mitigate the issues are recommended.

EEG-Based BCI Emotion Recognition: A Survey

“…Model frameworks can categorize classification algorithms [ 56 , 57 ]. The model’s categories may be (1) generative-discriminative, (2) static-dynamic, (3) stable-unstable, and (4) regularized [ 102 , 103 , 104 ].…”

Progress in Brain Computer Interface: Challenges and Opportunities

“…This overview encompasses a wide range of challenges and trends in BCI field. For specialized reviews on particular BCI topics we refer to the recent literature (McFarland et al, 2006 ; Schwartz et al, 2006 ; Bashashati et al, 2007 ; Lotte et al, 2007 , 2018 ; Matthews et al, 2007 ; Sitaram et al, 2007 ; Mak and Wolpaw, 2009 ; Menon et al, 2009 ; Nicolelis and Lebedev, 2009 ; Summerer et al, 2009 ; Vaadia and Birbaumer, 2009 ; Milan and Carmena, 2010 ; Min et al, 2010 ; Clausen, 2011 ; Krusienski et al, 2011 ; Liao et al, 2012 ; Nicolas-Alonso and Gomez-Gil, 2012 ; Shih et al, 2012 ; Jebari, 2013 ; McCullagh et al, 2014 ; Ahn and Jun, 2015 ; Jayaram et al, 2016 ; Lebedev and Nicolelis, 2017 ; Mudgal et al, 2020 ; Rashid et al, 2020 ; Saha and Baumert, 2020 ).…”

The Use of Brain–Computer Interfaces in Games Is Not Ready for the General Public

“…The game also demonstrates a good understanding of game design by naturally incorporating visual stimulations in the virtual environment. In this respect, Kaplan et al (2013), Cattan et al (2018b), and Rashid et al (2020) provided a set of guidelines to adapt game implementation for BCI games, such as the use of turn-based games with a slow gameplay. Although Brain Invaders use a research-grade amplifier, the feasibility of using a low-cost EEG acquisition system for BCI has been demonstrated by Vos et al (2014) and Yohanandan et al (2018).…”