Brain computer interface: control signals review

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• 作者：Rabie A. Ramadan^a ; ^b ; ^{rabie@rabieramadan.org}Author Vitae ; Athanasios V. Vasilakos^c ; ^{th.vasilakos@gmail.com}Author Vitae
• 关键词：Brain computer interface ; BCI ; BCI signals ; BCI technology ; Hardware ; Software ; BCI challenges ; Future directions
• 刊名：Neurocomputing
• 出版年：2017
• 出版时间：5 February 2017
• 年：2017
• 卷：223
• 期：Complete
• 页码：26-44
• 全文大小：1700 K
• 卷排序：223

文摘

Brain Computer Interface (BCI) is defined as a combination of hardware and software that allows brain activities to control external devices or even computers. The research in this field has attracted academia and industry alike. The objective is to help severely disabled people to live their life as regular persons as much as possible. Some of these disabilities are categorized as neurological neuromuscular disorders. A BCI system goes through many phases including preprocessing, feature extraction, signal classifications, and finally control. Large body of research are found at each phase and this might confuse researchers and BCI developers. This article is a review to the state-of-the-art work in the field of BCI. The main focus of this review is on the Brain control signals, their types and classifications. In addition, this survey reviews the current BCI technology in terms of hardware and software where the most used BCI devices are described as well as the most utilized software platforms are explained. Finally, BCI challenges and future directions are stated. Due to the limited space and large body of literature in the field of BCI, another two review articles are planned. One of these articles reviews the up-to-date BCI algorithms and techniques for signal processing, feature extraction, signals classification, and control. Another article will be dedicated to BCI systems and applications. The three articles are written as base and guidelines for researchers and developers pursue the work in the field of BCI.