Open AccessA review on elicit potentials in the brain to recognize Brain-Machine interface
Author(s) -
Mohd Rizwan Jafar,
Ashish Kumar Srivastava
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/2007/1/012048
Subject(s) - interface (matter) , computer science , brain–computer interface , human–machine interface , state (computer science) , signal (programming language) , feature (linguistics) , human–computer interaction , feature extraction , artificial intelligence , machine learning , human–machine system , neuroscience , electroencephalography , psychology , programming language , bubble , maximum bubble pressure method , linguistics , philosophy , parallel computing
Brain-machine interface is a technique with the help of which a user can generate a control signal to operate a machine by manipulating its state of cognition. In this technique, electrical signals generated in the central/peripheral nervous system are used to generate commands to interact with machines. In this paper, authors reviewed this technique in detail to find out the state of the art. This paper is written in such a way that a beginner can understand what a brain machine actually is. In this paper different types of methods to elicit signals for brain machine interface is explained along with different types of methods to record the signals. It is also described the state of the art in feature extraction and classification methods used in brain machine interface.