Open AccessVarious signals used for device navigation in BCI production
Author(s) -
Ravichander Janapati,
Viswas Dalal,
Rakesh sen gupta,
P. Anuradha,
P. V. Raja Shekar
Publication year - 2020
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/981/3/032003
Subject(s) - brain–computer interface , computer science , electroencephalography , human–computer interaction , interface (matter) , virtual reality , psychology , neuroscience , bubble , maximum bubble pressure method , parallel computing
With computer hardware development in recent years it has become easier than in earlier centuries to resolve problems in machine learning and computer vision. This has led to a widespread interest in EEG-based brain computer (EEG-BCI) interfaces, which can be used to support a number of support technologies which benefit from the hands-free and personal thought translation in this area. However, most analysis is more practical than evidence-of-concept. Therefore, some technological advances are being developed to allow seriously weakened engine systems to be used temporally in a 2D or 3D virtual environment, such as multiple sclerosis, amyotrophic lateral sclerosis, New technologies and rising developments in automation technologies, In bringing new technology to a continuously diverse population, we are confronted with new challenges. However, in recent years no one has studied general patterns for web applications with different aspects of the BCI interface architecture. In this study, we examined how EEG-BCI research has developed over the past decade to explore the latest trends in EEG applications. In this article, we have researched the review of articles BCI articles for each signals and functionality.