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. 2017 Apr 28;12(4):e0176674.
doi: 10.1371/journal.pone.0176674. eCollection 2017.

A systematic review of hybrid brain-computer interfaces: Taxonomy and usability perspectives

Inchul Choi  1 , Ilsun Rhiu  2 , Yushin Lee  3 , Myung Hwan Yun  3 , Chang S Nam  1
Affiliations

A systematic review of hybrid brain-computer interfaces: Taxonomy and usability perspectives

Inchul Choi et al. PLoS One. .

Abstract

A new Brain-Computer Interface (BCI) technique, which is called a hybrid BCI, has recently been proposed to address the limitations of conventional single BCI system. Although some hybrid BCI studies have shown promising results, the field of hybrid BCI is still in its infancy and there is much to be done. Especially, since the hybrid BCI systems are so complicated and complex, it is difficult to understand the constituent and role of a hybrid BCI system at a glance. Also, the complicated and complex systems make it difficult to evaluate the usability of the systems. We systematically reviewed and analyzed the current state-of-the-art hybrid BCI studies, and proposed a systematic taxonomy for classifying the types of hybrid BCIs with multiple taxonomic criteria. After reviewing 74 journal articles, hybrid BCIs could be categorized with respect to 1) the source of brain signals, 2) the characteristics of the brain signal, and 3) the characteristics of operation in each system. In addition, we exhaustively reviewed recent literature on usability of BCIs. To identify the key evaluation dimensions of usability, we focused on task and measurement characteristics of BCI usability. We classified and summarized 31 BCI usability journal articles according to task characteristics (type and description of task) and measurement characteristics (subjective and objective measures). Afterwards, we proposed usability dimensions for BCI and hybrid BCI systems according to three core-constructs: Satisfaction, effectiveness, and efficiency with recommendations for further research. This paper can help BCI researchers, even those who are new to the field, can easily understand the complex structure of the hybrid systems at a glance. Recommendations for future research can also be helpful in establishing research directions and gaining insight in how to solve ergonomics and HCI design issues surrounding BCI and hybrid BCI systems by usability evaluation.

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Conflict of interest statement

Competing Interests: The authors declare that no competing interests exist.

Figures

Fig 1
Fig 1. PRISMA flow diagram of hybrid BCIs.
Fig 2
Fig 2. Flow diagram of taxonomy for hybrid BCIs.
Fig 3
Fig 3. Schematic diagram for three different roles of operation.
Fig 4
Fig 4. PRISMA flow diagram of usability of BCI.
Fig 5
Fig 5. Usability dimensions for BCI systems.
See this image and copyright information in PMC

References

    1. Wolpaw JR, Birbaumer N, Heetderks WJ, McFarland DJ, Peckham PH, Schalk G, et al. Brain-computer interface technology: a review of the first international meeting. IEEE Trans Rehabil Eng. 2000;8: 164–173. - PubMed
    1. Allison BZ, Wolpaw EW, Wolpaw JR. Brain-computer interface systems: progress and prospects. Expert Rev Med Devices. Taylor & Francis; 2007;4: 463–474. doi: 10.1586/17434440.4.4.463 - DOI - PubMed
    1. Nijholt A, Tan D, Pfurtscheller G, Brunner C, Millán J del R, Allison BZ, et al. Brain-computer interfacing for intelligent systems. IEEE Intell Syst. IEEE; 2008;23: 72–79.
    1. Allison BZ, Leeb R, Brunner C, Müller-Putz GR, Bauernfeind G, Kelly JW, et al. Toward smarter BCIs: extending BCIs through hybridization and intelligent control. J Neural Eng. 2011/12/14. 2012;9: 13001. - PubMed
    1. Nam CS, Woo J, Bahn S. Severe motor disability affects functional cortical integration in the context of brain-computer interface (BCI) use. Ergonomics. 2012;55: 581–91. doi: 10.1080/00140139.2011.647095 - DOI - PubMed

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