Brain-Computer Interfaces (BCIs) are technologies that create direct communication pathways between the brain and external devices. Sensor technology plays a crucial role in this field, as it allows for the accurate detection and interpretation of neural signals. By advancing sensor technology, we can improve the performance, usability, and accessibility of BCI systems.
This Research Topic aims to gather research focusing on the development, evaluation, and application of sensor technologies in BCIs. Our goal is to cover a wide range of innovations that contribute to making BCIs more efficient, user-friendly, and applicable in real-world scenarios.
Topics of interest include but are not limited to:
Improvements in non-invasive sensors, including EEG, MEG, and fNIRS.
Development of implantable sensors with long-term stability and biocompatibility.
Methods for noise reduction and signal enhancement.
Machine learning techniques for pattern recognition and signal interpretation.
BCIs for neurorehabilitation and treatment of neurological disorders.
Assistive technologies for individuals with mobility or communication impairments.
Emerging trends in sensor technology and their potential impact on BCIs.
Bio-computational modeling design for BCIs/Impact of bio-computational modeling on BCIs
Keywords:
BCI, sensor technology, biocompatibility, neurorehabilitation, bio-computational modeling
Important Note:
All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.
Brain-Computer Interfaces (BCIs) are technologies that create direct communication pathways between the brain and external devices. Sensor technology plays a crucial role in this field, as it allows for the accurate detection and interpretation of neural signals. By advancing sensor technology, we can improve the performance, usability, and accessibility of BCI systems.
This Research Topic aims to gather research focusing on the development, evaluation, and application of sensor technologies in BCIs. Our goal is to cover a wide range of innovations that contribute to making BCIs more efficient, user-friendly, and applicable in real-world scenarios.
Topics of interest include but are not limited to:
Improvements in non-invasive sensors, including EEG, MEG, and fNIRS.
Development of implantable sensors with long-term stability and biocompatibility.
Methods for noise reduction and signal enhancement.
Machine learning techniques for pattern recognition and signal interpretation.
BCIs for neurorehabilitation and treatment of neurological disorders.
Assistive technologies for individuals with mobility or communication impairments.
Emerging trends in sensor technology and their potential impact on BCIs.
Bio-computational modeling design for BCIs/Impact of bio-computational modeling on BCIs
Keywords:
BCI, sensor technology, biocompatibility, neurorehabilitation, bio-computational modeling
Important Note:
All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.