Abstract
This study reviews the originality and development of the Brain Computer Interface (BCI) system and focus on the BCI system design based on Blind Source Separation (BSS) techniques. The study also provides the recent trends and discusses some of a new ideas for BSS techniques in BCI architecture, articles which discussing the BCI system development were analysed, types of the BCI systems and the recent BCI design were explored. Since 1970 when the research of BCI system began in the California Los Angeles University, the interest and the amount of research in BCI have been increased significantly; especially, when the BSS theory emerged in 1982 by a simple discussion between researchers. A lot of refereed journals and conference papers are reviewed and categorized to make this study in useful form. However, there are a few comprehensive reviews of BSS techniques in BCI literature. The review concludes with a brief discussion and expected future of the BCI.
Highlights
Brain Computer Interface (BCI) is a communication system that translates the user’s intent into control signals
This review study is a useful for the researchers to develop the BCI systems and determine further research areas in the field
Independent Component Analysis (ICA): ICA has usually been used as a preprocessing technique before the feature extraction step, to remove the artifacts in BCI (Flexer et al, 2005; Gao et al, 2010)
Summary
Brain Computer Interface (BCI) is a communication system that translates the user’s intent into control signals. BCI system consists of 4 sequential components: Fig. 3: Brain signal analysis: Blind source separation problem (Tahir, 2010). They represent one of the limitations in the signal acquisition unit of brain computer interface system, most significant of which are: Ballistocardiogram (BCG), Electrooculogram (EOG), Electromyographic (EMG) and line artifacts, (Tahir, 2010) They may change the characteristics of neurological phenomena or even be mistakenly used as the source of control in BCI systems (Mehrdad et al, 2007). Erfanian and Erfani (2004) are used ICA approach to design a new EEG-based BCI for natural control of prosthetic hand grasp and suggest the possibility of using ICA to separate different independent brain activities during motor imagery into separate components.
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