%0 Journal Article
%T A Review of Hybrid Brain-Computer Interface Systems
%A Setare Amiri
%A Reza Fazel-Rezai
%A Vahid Asadpour
%J Advances in Human-Computer Interaction
%D 2013
%I Hindawi Publishing Corporation
%R 10.1155/2013/187024
%X Increasing number of research activities and different types of studies in brain-computer interface (BCI) systems show potential in this young research area. Research teams have studied features of different data acquisition techniques, brain activity patterns, feature extraction techniques, methods of classifications, and many other aspects of a BCI system. However, conventional BCIs have not become totally applicable, due to the lack of high accuracy, reliability, low information transfer rate, and user acceptability. A new approach to create a more reliable BCI that takes advantage of each system is to combine two or more BCI systems with different brain activity patterns or different input signal sources. This type of BCI, called hybrid BCI, may reduce disadvantages of each conventional BCI system. In addition, hybrid BCIs may create more applications and possibly increase the accuracy and the information transfer rate. However, the type of BCIs and their combinations should be considered carefully. In this paper, after introducing several types of BCIs and their combinations, we review and discuss hybrid BCIs, different possibilities to combine them, and their advantages and disadvantages. 1. Introduction A brain-computer interface (BCI) system can provide a communication method to convey brain messages independent from the brainĄ¯s normal output pathway [1]. Brain activity can be monitored using different approaches such as standard scalp-recording electroencephalogram (EEG), magnetoencephalogram (MEG), functional magnetic resonance imaging (fMRI), electrocorticogram (ECoG), and near infrared spectroscopy (NIRS) [1¨C4]. However, EEG signals are considered as the input in most BCI systems. In this case, BCI systems are categorized based on the brain activity patterns such as event-related desynchronization/synchronization (ERD/ERS), steady-state visual evoked potentials (SSVEPs), P300 component of event related potentials (ERPs), and slow cortical potentials (SCPs) [5¨C16]. Each BCI type has its own shortcoming and disadvantages. To utilize the advantages of different types of BCIs, different approaches are combined, called hybrid BCIs [15, 16]. In a hybrid BCI, two types of BCI systems can be combined. It is also possible to combine one BCI system with another system which is not BCI-based, for example, combining a BCI system with an electromyogram (EMG)-based system. However, one can debate if this type of system should be defined as hybrid BCI. In the rest of this paper, we assume that if an EEG BCI system is combined with another physiological
%U http://www.hindawi.com/journals/ahci/2013/187024/