A Review of Hybrid Brain-Computer Interface Systems

Setare Amiri,Vahid Asadpour,Reza Fazel-Rezai

doi:10.1155/2013/187024

Setare Amiri, Vahid Asadpour + Show 1 more

Open Access

https://doi.org/10.1155/2013/187024

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Abstract

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.

Highlights

A brain-computer interface (BCI) system can provide a communication method to convey brain messages independent from the brain’s normal output pathway [1]
There are several advantages of sequential combination when one of the BCIs is used as a switch or different BCIs are used for different tasks sequentially
In [16], one BCI (ERD) was used as a switch for another BCI (SSVEP) and the false positive rate was decreased for this sequential hybrid BCI

Summary

Introduction

A brain-computer interface (BCI) system can provide a communication method to convey brain messages independent from the brain’s normal output pathway [1]. 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) [5,6,7,8,9,10,11,12,13,14,15,16]. In non-hybrid BCIs, based on the property of EEG signals used as the input of BCI system, four major EEG-based BCIs are considered: SSVEP, P300, SCP, and ERD/ERS. Positive and negative deflections occur in the EEG These deflections are called event-related potential (ERP) components. ERD/ERS BCIs have been used in different applications such as achieving two-dimensional cursor control

Hybrid BCI Systems

Review of Different Hybrid BCIs

Findings

Conclusion