Results 41 to 50 of about 378,811 (361)
Manifold Embedded Knowledge Transfer for Brain-Computer Interfaces [PDF]
IEEE transactions on neural systems and rehabilitation engineering, 2019 Transfer learning makes use of data or knowledge in one problem to help solve a different, yet related, problem. It is particularly useful in brain-computer interfaces (BCIs), for coping with variations among different subjects and/or tasks.
Wen Zhang, Dongrui Wu
semanticscholar +1 more source
Towards hippocampal navigation for brain–computer interfaces
Scientific Reports, 2023 Automatic wheelchairs directly controlled by brain activity could provide autonomy to severely paralyzed individuals. Current approaches mostly rely on non-invasive measures of brain activity and translate individual commands into wheelchair movements ...
Jeremy Saal +7 more
doaj +1 more source
IEEE transactions on neural systems and rehabilitation engineering, 2020 In recent years, deep-learning models gained attention for electroencephalography (EEG) classification tasks due to their excellent performance and ability to extract complex features from raw data.
E. Santamaría-Vázquez +3 more
semanticscholar +1 more source
Brain–Computer Interfaces in Neurorecovery and Neurorehabilitation
Seminars in neurology, 2021 Recent advances in brain–computer interface technology to restore and rehabilitate neurologic function aim to enable persons with disabling neurologic conditions to communicate, interact with the environment, and achieve other key activities of daily ...
Michael J. Young +2 more
semanticscholar +1 more source
Flexible Neural Electrode Array Based-on Porous Graphene for Cortical Microstimulation and Sensing. [PDF]
, 2016 Neural sensing and stimulation have been the backbone of neuroscience research, brain-machine interfaces and clinical neuromodulation therapies for decades.
Kuzum, Duygu +4 more
core +2 more sources
Neurotechnologies for Human Cognitive Augmentation: Current State of the Art and Future Prospects
Frontiers in Human Neuroscience, 2019 Recent advances in neuroscience have paved the way to innovative applications that cognitively augment and enhance humans in a variety of contexts. This paper aims at providing a snapshot of the current state of the art and a motivated forecast of the ...
Caterina Cinel +3 more
doaj +1 more source
Neural–Computer Interfaces: Theory, Practice, Perspectives
Applied SciencesThis review outlines the technological principles of neural–computer interface (NCI) construction, classifying them according to: (1) the degree of intervention (invasive, semi-invasive, and non-invasive); (2) the direction of signal communication ...
Ignat Dubynin +5 more
doaj +1 more source
Brain–Computer Interfaces for Human Augmentation
Brain Sciences, 2019 The field of brain⁻computer interfaces (BCIs) has grown rapidly in the last few decades, allowing the development of ever faster and more reliable assistive technologies for converting brain activity into control signals for external devices for ...
Davide Valeriani +2 more
doaj +1 more source
Multi-Armed Bandits in Brain-Computer Interfaces
Frontiers in Human Neuroscience, 2022 The multi-armed bandit (MAB) problem models a decision-maker that optimizes its actions based on current and acquired new knowledge to maximize its reward.
Frida Heskebeck +2 more
doaj +1 more source
EEG-Based Brain-Computer Interfaces Using Motor-Imagery: Techniques and Challenges
Italian National Conference on Sensors, 2019 Electroencephalography (EEG)-based brain-computer interfaces (BCIs), particularly those using motor-imagery (MI) data, have the potential to become groundbreaking technologies in both clinical and entertainment settings.
Natasha M. J. Padfield +4 more
semanticscholar +1 more source