Abstract
This review article provides a deep insight into the Brain–Computer Interface (BCI) and the application of Machine Learning (ML) technology in BCIs. It investigates the various types of research undertaken in this realm and discusses the role played by ML in performing different BCI tasks. It also reviews the ML methods used for mental state detection, mental task categorization, emotion classification, electroencephalogram (EEG) signal classification, event-related potential (ERP) signal classification, motor imagery categorization, and limb movement classification. This work explores the various methods employed in BCI mechanisms for feature extraction, selection, and classification and provides a comparative study of reviewed methods. This paper assists the readers to gain information regarding the developments made in BCI and ML domains and future improvements needed for improving and designing better BCI applications.
Highlights
In the last few years, vast developments have occurred in automated control and monitoring applications
It has reviewed various Brain–Computer Interface (BCI)-related studies and described the role played by Machine Learning (ML) towards diverse BCI tasks such as motor imagery (MI) classification, emotion classification, and mental state and mental task classification
It has explored diverse feature extraction, selection, and classification schemes exploited in the literature for classification of EEG, event-related potential (ERP) signals, mental state, mental task, limb motion, emotion, and MI
Summary
In the last few years, vast developments have occurred in automated control and monitoring applications. BCI is a breakthrough innovation in the domain of brain mapping It generally interprets the message of neurons and employs it for executing the tasks [1]. This direct bridge between the machine and the brain has numerous applications in the medication domain for physically disabled or locked-in people. BCI connects the human brain with peripheral devices by creating a direct interacting link between the outer world and the brain and creating a bi-directional communication interface between the outer environment and the brain They provide a muscle-free medium for conveying persons’ purposes of actions to outer/external devices such as computers, neural prostheses, and other assistive appliances. Unlike the classical input devices such as keyboard, pen, and mouse, the BCI reads the signals generated from the human brain at distinct locations, translates them into actions and commands through which computer(s) can be controlled for executing desired control/monitoring tasks [2]
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
