| Literature DB >> 32581758 |
Mamunur Rashid1, Norizam Sulaiman1, Anwar P P Abdul Majeed2, Rabiu Muazu Musa3, Ahmad Fakhri Ab Nasir2, Bifta Sama Bari1, Sabira Khatun1.
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.Entities:
Keywords: brain-computer interface (BCI); classification; electroencephalogram (EEG); feature extraction; machine learning
Year: 2020 PMID: 32581758 PMCID: PMC7283463 DOI: 10.3389/fnbot.2020.00025
Source DB: PubMed Journal: Front Neurorobot ISSN: 1662-5218 Impact factor: 2.650