Volume 9, Issue 5 (September & October 2018 2018)                   BCN 2018, 9(5): 373-388 | Back to browse issues page


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Sadeghi S, Maleki A. Recent Advances in Hybrid Brain-Computer Interface Systems: A Technological and Quantitative Review. BCN. 2018; 9 (5) :373-388
URL: http://bcn.iums.ac.ir/article-1-960-en.html
1- Department of Biomedical Engineering, Faculty of New Sciences and Technologies, Semnan University, Semnan, Iran.
Abstract:  

Brain-Computer Interface (BCI) is a system that enables users to transmit commands to the computer using their brain activity recorded by electroencephalography. In a Hybrid Brain-Computer Interface (HBCI), a BCI control signal combines with one or more BCI control signals or with Human-Machine Interface (HMI) biosignals to increase classification accuracy, boost system speed, and improve user’s satisfaction. HBCI systems are categorized according to the type of combined signals and the combination technique (simultaneous or sequential). They have been used in several applications such as cursor control, target selection, and spellers. Increasing the number of articles published in this field indicates the significance of these systems. In this paper, different HBCI combinations, their important features, and potential applications are discussed. In most cases, the combination of a BCI control signal with a HMI biosignal yields higher information transfer rate than two BCI control signals.

Type of Study: Methodological Notes | Subject: Computational Neuroscience
Received: 2017/06/6 | Accepted: 2018/05/29 | Published: 2018/09/1

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