A hybrid NIRS-EEG system for self-paced brain computer interface with online motor imagery

Koo, Bonkon; Lee, Hwan-Gon; Nam, Yunjun; Kang, Hyohyeong; Koh, Chin Su; Shin, Hyung‐Cheul; Choi, Seungjin

doi:10.1016/j.jneumeth.2014.04.016

Cited by 108 publications

(88 citation statements)

References 20 publications

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“…Recently, many BCI studies are focusing on on-line BCI and on-line implementation is essential to confirm the practical usability of BCI paradigm295455. We evaluated the feasibility of NIRS-based EC BCI as an alternative of conventional BCI paradigms and performed off-line analyses.…”

Section: Discussionmentioning

confidence: 99%

Near-infrared spectroscopy (NIRS)-based eyes-closed brain-computer interface (BCI) using prefrontal cortex activation due to mental arithmetic

Shin

Müller

Hwang

2016

Sci Rep

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We propose a near-infrared spectroscopy (NIRS)-based brain-computer interface (BCI) that can be operated in eyes-closed (EC) state. To evaluate the feasibility of NIRS-based EC BCIs, we compared the performance of an eye-open (EO) BCI paradigm and an EC BCI paradigm with respect to hemodynamic response and classification accuracy. To this end, subjects performed either mental arithmetic or imagined vocalization of the English alphabet as a baseline task with very low cognitive loading. The performances of two linear classifiers were compared; resulting in an advantage of shrinkage linear discriminant analysis (LDA). The classification accuracy of EC paradigm (75.6 ± 7.3%) was observed to be lower than that of EO paradigm (77.0 ± 9.2%), which was statistically insignificant (p = 0.5698). Subjects reported they felt it more comfortable (p = 0.057) and easier (p < 0.05) to perform the EC BCI tasks. The different task difficulty may become a cause of the slightly lower classification accuracy of EC data. From the analysis results, we could confirm the feasibility of NIRS-based EC BCIs, which can be a BCI option that may ultimately be of use for patients who cannot keep their eyes open consistently.

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Section: Discussionmentioning

confidence: 99%

Near-infrared spectroscopy (NIRS)-based eyes-closed brain-computer interface (BCI) using prefrontal cortex activation due to mental arithmetic

Shin

Müller

Hwang

2016

Sci Rep

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“…Recently, there has been a growing interest in the NFB community to combine more than one brain activity measurement technology (Nakano et al, 2012; Yu et al, 2013; Jorge et al, 2014; Koo et al, 2015), where the combination of EEG and fMRI seems to be the most notable. For instance, fMRI has been used as the second complementary data in the EEG inverse problem (Grech et al, 2008) to localize the origins of the neuronal activity.…”

Section: Introductionmentioning

confidence: 99%

How to Build a Hybrid Neurofeedback Platform Combining EEG and fMRI

et al. 2017

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Multimodal neurofeedback estimates brain activity using information acquired with more than one neurosignal measurement technology. In this paper we describe how to set up and use a hybrid platform based on simultaneous electroencephalography (EEG) and functional magnetic resonance imaging (fMRI), then we illustrate how to use it for conducting bimodal neurofeedback experiments. The paper is intended for those willing to build a multimodal neurofeedback system, to guide them through the different steps of the design, setup, and experimental applications, and help them choose a suitable hardware and software configuration. Furthermore, it reports practical information from bimodal neurofeedback experiments conducted in our lab. The platform presented here has a modular parallel processing architecture that promotes real-time signal processing performance and simple future addition and/or replacement of processing modules. Various unimodal and bimodal neurofeedback experiments conducted in our lab showed high performance and accuracy. Currently, the platform is able to provide neurofeedback based on electroencephalography and functional magnetic resonance imaging, but the architecture and the working principles described here are valid for any other combination of two or more real-time brain activity measurement technologies.

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“…Также исполь-зование БИК является хорошим дополнением к ЭЭГ, по-зволяя улучшить результаты анализа биопотенциалов, по-высить прогностическую точность используемых моделей обработки информации и общую производительность ин-терфейса [82,83].…”

Section: неинвазивный интерфейс мозг-компьютерunclassified

The current state of the brain—computer interface problem

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et al. 2015

Vopr. neirokhir.

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A hybrid NIRS-EEG system for self-paced brain computer interface with online motor imagery

Cited by 108 publications

References 20 publications

Near-infrared spectroscopy (NIRS)-based eyes-closed brain-computer interface (BCI) using prefrontal cortex activation due to mental arithmetic

Near-infrared spectroscopy (NIRS)-based eyes-closed brain-computer interface (BCI) using prefrontal cortex activation due to mental arithmetic

How to Build a Hybrid Neurofeedback Platform Combining EEG and fMRI

The current state of the brain—computer interface problem

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