2018
DOI: 10.1109/jbhi.2017.2723024
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Effectiveness Evaluation of Real-Time Scalp Signal Separating Algorithm on Near-Infrared Spectroscopy Neurofeedback

Abstract: Near-infrared spectroscopy (NIRS), one of the candidates to be used in a neurofeedback system or brain-computer interface (BCI), measures the brain activity by monitoring the changes in cerebral hemoglobin concentration. However, hemodynamic changes in the scalp may affect the NIRS signals. In order to remove the superficial signals when NIRS is used in a neurofeedback system or BCI, real-time processing is necessary. Real-time scalp signal separating (RT-SSS) algorithm, which is capable of separating the scal… Show more

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Cited by 17 publications
(5 citation statements)
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“…However, because we captured only the frontal region, we can consider high density fNIRS to simultaneously investigate all potential cortical neuronal networks. Using a pulse oximeter and a short-distance measurement simultaneously could significantly minimize the scalp effect and systemic noise [54]. While we explored BBs at a single frequency of 16 Hz in this study, future research should investigate more frequencies.…”
Section: Discussionmentioning
confidence: 99%
“…However, because we captured only the frontal region, we can consider high density fNIRS to simultaneously investigate all potential cortical neuronal networks. Using a pulse oximeter and a short-distance measurement simultaneously could significantly minimize the scalp effect and systemic noise [54]. While we explored BBs at a single frequency of 16 Hz in this study, future research should investigate more frequencies.…”
Section: Discussionmentioning
confidence: 99%
“…Due to this constraint, MD-ICA cannot be used for real-time processing as required in NFB. Alternatively, (Ung et al 2017) examined the real-time scalp signal separating (RT-SSS) algorithm for the retrieval of reliable scalp signals. RT-SSS takes the source-detector (SD) distance into account.…”
Section: Nirs Based Nfbmentioning
confidence: 99%
“…Thus, the SC signals can be used as regressor for subsequent offline statistical analysis. The use of this approach in fNIRS-based NF studies is poorly documented [ 23 , 24 ] and to date, most of fNIRS-NF studies have been conducted without SC. Since the fNIRS-NF setup without SC might be better suited for clinical purposes, it is thus important to investigate the link between online NF signal without SC, experienced by the participants, and the offline SC-corrected signal, which can be more reflective of accurate neuronal activation.…”
Section: Introductionmentioning
confidence: 99%