A systematic review on hybrid EEG/fNIRS in brain-computer interface. (July 2021)

• Record Type: Journal Article
• Authors: Liu, Ziming; Shore, Jeremy; Wang, Miao; Yuan, Fengpei; Buss, Aaron; Zhao, Xiaopeng
• Is Part Of: Biomedical signal processing and control. Volume 68(2021)
• Publication Date: 2021-07
• Subjects: Brain-computer interface -- Hybrid neuroimaging -- EEG/fNIRS -- Systematic review; Signal processing -- Periodicals; Biomedical engineering -- Periodicals; Signal Processing, Computer-Assisted -- Periodicals; Image Processing, Computer-Assisted -- Periodicals; Biomedical Engineering -- Periodicals; 610.28
• DOI: 10.1016/j.bspc.2021.102595
• Languages: English
• ISSNs: 1746-8094

Abstract

Abstract: As a relatively new field of neurology and computer science, brain computer interface (BCI) has many established and burgeoning applications across scientific disciplines. Many neural monitoring technologies have been developed for BCI studies. Combining multiple monitoring technologies provides a new approach that synthesizes the advantages and overcomes the limitations of each technology. This article presents a systematic review on the applications, limitations, and future directions for the hybridization of electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) into one synchronous multimodality. This review investigated research questions on design and usability of hybrid EEG-fNIRS studies. In this article, 765 papers were included in the initial search and 128 papers were selected through the PRISMA protocol. The review results show the possibility of improving the performance of hybrid EEG-fNIRS by optimizing the feature extraction algorithms and physical designing as well as expending more possible applications in information processing related fields.