Brain-Computer Interfaces (BCIs) have received special attention the last two decades both for clinical and everyday activities. A BCI scheme involves the control of surroundings without a tangible means of interaction, only by utilizing the brain activity captured with various technologies. Several brain imaging technologies have been used to capture the brain activity in a BCI framework including, electroencephalography (EEG), magnetoencephalography (MEG), functional Magnetic Resonance Imaging (fMRI) and others. Relatively recently, a new technology, namely, Near-Infrared Spectroscopy (NIRS) has opened new possibilities for efficient BCI systems. NIRS uses light source-detector pairs in the near-infrared range and measures hemodynamic changes related to the concentration changes of the chromophore hemoglobin. As an oxygen carrier, hemoglobin‘s concentration increases during various mental tasks due to elevated neuronal activation. Thus, one can perform a mental task, e.g., arithmetic subtraction, at will in order to control a cursor within a BCI mouse realization using only his brain activity.
This Research Topic’s aim is to provide a collection of forefront works investigating all aspects of a NIRS-based BCI system (NIRS-BCI), i.e., NIRS signal recording within various mental tasks, e.g., imaginary movement, mental subtraction, music imagination etc., NIRS signal preprocessing, noise cancelation and artifact removal, feature extraction, and classification. Submitted works can describe BCI systems employed in either a laboratory setting or in a real-world environment. Moreover, they can relate to clinical conditions or non-clinical ones demonstrating BCI functionality with everyday activities.
Topics of interest include, but are not limited to:
- NIRS-based Motor Cortex activities recognition (e.g., motor imagery)
- Motor Rehabilitation NIRS-BCIs
- NIRS-based Prefrontal Cortex activities recognition (e.g., mental arithmetic)
- Affective NIRS-BCIs
- Passive NIRS-BCIs
- Temporal/Spatiotemporal dynamics of NIRS-BCIs
- NIRS artifact removal methods for efficient BCIs
- Augmented Reality and Virtual Reality NIRS-BCIs
- NIRS-BCIs in games
- Hybrid BCIs, e.g., NIRS/EEG, NIRS/MEG etc.
- Multi-Brain Interaction NIRS-BCIs
Brain-Computer Interfaces (BCIs) have received special attention the last two decades both for clinical and everyday activities. A BCI scheme involves the control of surroundings without a tangible means of interaction, only by utilizing the brain activity captured with various technologies. Several brain imaging technologies have been used to capture the brain activity in a BCI framework including, electroencephalography (EEG), magnetoencephalography (MEG), functional Magnetic Resonance Imaging (fMRI) and others. Relatively recently, a new technology, namely, Near-Infrared Spectroscopy (NIRS) has opened new possibilities for efficient BCI systems. NIRS uses light source-detector pairs in the near-infrared range and measures hemodynamic changes related to the concentration changes of the chromophore hemoglobin. As an oxygen carrier, hemoglobin‘s concentration increases during various mental tasks due to elevated neuronal activation. Thus, one can perform a mental task, e.g., arithmetic subtraction, at will in order to control a cursor within a BCI mouse realization using only his brain activity.
This Research Topic’s aim is to provide a collection of forefront works investigating all aspects of a NIRS-based BCI system (NIRS-BCI), i.e., NIRS signal recording within various mental tasks, e.g., imaginary movement, mental subtraction, music imagination etc., NIRS signal preprocessing, noise cancelation and artifact removal, feature extraction, and classification. Submitted works can describe BCI systems employed in either a laboratory setting or in a real-world environment. Moreover, they can relate to clinical conditions or non-clinical ones demonstrating BCI functionality with everyday activities.
Topics of interest include, but are not limited to:
- NIRS-based Motor Cortex activities recognition (e.g., motor imagery)
- Motor Rehabilitation NIRS-BCIs
- NIRS-based Prefrontal Cortex activities recognition (e.g., mental arithmetic)
- Affective NIRS-BCIs
- Passive NIRS-BCIs
- Temporal/Spatiotemporal dynamics of NIRS-BCIs
- NIRS artifact removal methods for efficient BCIs
- Augmented Reality and Virtual Reality NIRS-BCIs
- NIRS-BCIs in games
- Hybrid BCIs, e.g., NIRS/EEG, NIRS/MEG etc.
- Multi-Brain Interaction NIRS-BCIs
