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

Mamunur Rashid*, Norizam Sulaiman, Anwar P. P. Abdul Majeed, Rabiu Muazu Musa, Ahmad Fakhri Ahmad, Bifta Sama Bari, Sabira Khatun

*Corresponding author for this work

Research output: Contribution to journalReview articlepeer-review

254 Citations (Scopus)

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.

Original languageEnglish
Article number25
JournalFrontiers in Neurorobotics
Volume14
DOIs
Publication statusPublished - 3 Jun 2020
Externally publishedYes

Keywords

  • brain-computer interface (BCI)
  • classification
  • electroencephalogram (EEG)
  • feature extraction
  • machine learning

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