Riemannian approaches in brain-computer interfaces: a review
Although promising from numerous applications, current brain-computer interfaces (BCIs)
still suffer from a number of limitations. In particular, they are sensitive to noise, outliers and …
still suffer from a number of limitations. In particular, they are sensitive to noise, outliers and …
Simultaneously optimizing spatial spectral features based on mutual information for EEG classification
High performance of the brain-computer interface (BCI) needs efficient algorithms to extract
discriminative features from raw electroencephalography (EEG) signals. In this paper, we …
discriminative features from raw electroencephalography (EEG) signals. In this paper, we …
[HTML][HTML] Concurrent fNIRS and EEG for brain function investigation: a systematic, methodology-focused review
Electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) stand as
state-of-the-art techniques for non-invasive functional neuroimaging. On a unimodal basis …
state-of-the-art techniques for non-invasive functional neuroimaging. On a unimodal basis …
Brain–machine interfaces using functional near-infrared spectroscopy: a review
Functional near-infrared spectroscopy (fNIRS) is a noninvasive method for acquiring
hemodynamic signals from the brain with advantages of portability, affordability, low …
hemodynamic signals from the brain with advantages of portability, affordability, low …
Comparative analysis of strategies for feature extraction and classification in SSVEP BCIs
Brain–computer interface (BCI) systems based on electroencephalography have been
increasingly used in different contexts, engendering applications from entertainment to …
increasingly used in different contexts, engendering applications from entertainment to …
[HTML][HTML] Using the general linear model to improve performance in fNIRS single trial analysis and classification: a perspective
A von Lühmann, A Ortega-Martinez… - Frontiers in human …, 2020 - frontiersin.org
Within a decade, single trial analysis of functional Near Infrared Spectroscopy (fNIRS)
signals has gained significant momentum, and fNIRS joined the set of modalities frequently …
signals has gained significant momentum, and fNIRS joined the set of modalities frequently …
Investigating deep learning for fNIRS based BCI
Functional Near infrared Spectroscopy (fNIRS) is a relatively young modality for measuring
brain activity which has recently shown promising results for building Brain Computer …
brain activity which has recently shown promising results for building Brain Computer …
[HTML][HTML] Hybrid fNIRS-EEG based classification of auditory and visual perception processes
For multimodal Human-Computer Interaction (HCI), it is very useful to identify the modalities
on which the user is currently processing information. This would enable a system to select …
on which the user is currently processing information. This would enable a system to select …
Online binary decision decoding using functional near-infrared spectroscopy for the development of brain–computer interface
In this paper, a functional near-infrared spectroscopy (fNIRS)-based online binary decision
decoding framework is developed. Fourteen healthy subjects are asked to mentally make …
decoding framework is developed. Fourteen healthy subjects are asked to mentally make …
Evaluation of various mental task combinations for near-infrared spectroscopy-based brain-computer interfaces
A number of recent studies have demonstrated that near-infrared spectroscopy (NIRS) is a
promising neuroimaging modality for brain-computer interfaces (BCIs). So far, most NIRS …
promising neuroimaging modality for brain-computer interfaces (BCIs). So far, most NIRS …