Open AccessNon-Invasive Brain-Computer Interface Technology (BCI) Modalities and Implementation: A Review Article and Assimilation of BCI Models
Author(s) -
Dalia Mirghani Mahmoud Saadabi
Publication year - 2021
Publication title -
annals of advanced biomedical sciences
Language(s) - English
Resource type - Journals
ISSN - 2641-9459
DOI - 10.23880/aabsc-16000166
Subject(s) - brain–computer interface , computer science , interface (matter) , electroencephalography , modalities , human–computer interaction , field (mathematics) , artificial intelligence , psychology , neuroscience , social science , mathematics , bubble , maximum bubble pressure method , sociology , parallel computing , pure mathematics
Brain-computer interface (BCI) technology or brain-machine interface (BMI) technology has become the most attractive field for researchers in various disciplines and has occupied an important place in many scientific and even recreational applications. This review first highlights the different and most frequently used methods for implementing brain-computer interface (BCI) systems with a focus on non-invasive BCI models. Secondly, it analyzes the different stages of building a BCI system (input stage, signal processing stage, and output stage). Then it compares the different methods in terms of the algorithms used and the pros and cons. The aim of the study is to find the most adequate and price method to record the EEG by means of electrodes placed on the scalp. Then some features will be extracted from the EEG and sent to a classifier, whose response is translated features into some action whose execution provides feedback to the user.