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Proceedings ArticleDOI

Hybrid EEG-NIRS brain-computer interface under eyes-closed condition

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TLDR
The result demonstrated that the eyes-closed hybrid BCI approach could be potentially applied to neurodegenerative patients with impaired motor functions accompanied by a decline of visual functions.
Abstract
In this study, we propose a hybrid BCI combining electroencephalography (EEG) and near-infrared spectroscopy (NIRS) that can be potentially operated in eyes-closed condition for paralyzed patients with oculomotor dysfunctions In the experiment, seven healthy participants performed mental subtraction and stayed relaxed (baseline state), during which EEG and NIRS data were simultaneously measured To evaluate the feasibility of the hybrid BCI, we classified frontal brain activities inducted by mental subtraction and baseline state, and compared classification accuracies obtained using unimodal EEG and NIRS BCI and the hybrid BCI As a result, the hybrid BCI (8554 % ± 859) showed significantly higher classification accuracy than those of unimodal EEG (8077 % ± 1115) and NIRS BCI (7712 % ± 763) (Wilcoxon signed rank test, Bonferroni corrected p < 005) The result demonstrated that our eyes-closed hybrid BCI approach could be potentially applied to neurodegenerative patients with impaired motor functions accompanied by a decline of visual functions

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Citations
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Journal ArticleDOI

Multimodal exploration of non-motor neural functions in ALS patients using simultaneous EEG-fNIRS recording

TL;DR: A new dual-task multimodal framework relying on simultaneous electroencephalogram (EEG) and functional near-infrared spectroscopy (fNIRS) recordings was developed to characterize integrative non-motor neural functions in people with ALS and highlight the important role of ALS non-Motor dysfunctions in electrical and hemodynamic neural dynamics as well as their interrelationships.
References
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Journal ArticleDOI

Brain-computer interfaces for communication and control.

TL;DR: With adequate recognition and effective engagement of all issues, BCI systems could eventually provide an important new communication and control option for those with motor disabilities and might also give those without disabilities a supplementary control channel or a control channel useful in special circumstances.
Journal ArticleDOI

Single-Trial Analysis and Classification of ERP Components - a Tutorial

TL;DR: This tutorial proposes to use shrinkage estimators and shows that appropriate regularization of linear discriminant analysis (LDA) by shrinkage yields excellent results for single-trial ERP classification that are far superior to classical LDA classification.
Journal ArticleDOI

Enhanced performance by a hybrid NIRS–EEG brain computer interface

TL;DR: The results show that simultaneous measurements of NIRS and EEG can significantly improve the classification accuracy of motor imagery in over 90% of considered subjects and increases performance by 5% on average (p<0:01).
Journal ArticleDOI

Spatial spectra of scalp EEG and EMG from awake humans.

TL;DR: Spatial spectral peaks suggest that optimal scalp electrode spacing might be approximately 1cm to capture non-local EEG components having the texture of gyri, as an alternative to network approaches that decompose EEG into localized, modular signals for correlation and coherence.
Proceedings ArticleDOI

Automatic Removal of Ocular Artifacts in the EEG without an EOG Reference Channel

TL;DR: The proposed approach removed most EOG artifacts in 6 long-term EEG recordings containing epilectic seizures without distorting the recorded ictal activity.
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