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License: CC BY NC
Data sources: UnpayWall
https://doi.org/10.2991/emcs-1...
Article . 2016 . Peer-reviewed
Data sources: Crossref
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Review of Brain Computer Interface Components and Corresponding Research Topics

Authors: Rongjian Liang; Gang Li; Bin Liang; Xueqian Wang; Kang Wang;

Review of Brain Computer Interface Components and Corresponding Research Topics

Abstract

This paper conducts a research on the literature of Brain Computer Interface(BCI) in recent years, inducing the four components of BCI and the research topics respectively, and providing a guide to newcomers for exploring BCI. BCI is divided into four parts including signal collection, feature extraction, feature classification and practical application. Papers of above four parts are retrieved respectively from the SCI database. Topics of all papers are concluded, based on which the research topics of BCI are assigned to the four parts of BCI. In topics of each part of BCI, similar topics are summarized to the unique topic. Finally some research topics may cover dozens of papers while some topics may cover only several papers. In each of the four BCI components, there are several topics attracting most of the attention. BCI still has a great research value and good prospects for study. Keywords-Brain Computer Interface(BCI); signal collection; feature extraction; feature classification; practical application;

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
1
Average
Average
Average
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