Past, present, and future of EEG-based BCI applications
An electroencephalography (EEG)-based brain–computer interface (BCI) is a system that
provides a pathway between the brain and external devices by interpreting EEG. EEG …
provides a pathway between the brain and external devices by interpreting EEG. EEG …
Sensors and systems for physical rehabilitation and health monitoring—A review
LMS Nascimento, LV Bonfati, MLB Freitas… - Sensors, 2020 - mdpi.com
The use of wearable equipment and sensing devices to monitor physical activities, whether
for well-being, sports monitoring, or medical rehabilitation, has expanded rapidly due to the …
for well-being, sports monitoring, or medical rehabilitation, has expanded rapidly due to the …
EEG-based emotion recognition via transformer neural architecture search
C Li, Z Zhang, X Zhang, G Huang… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Emotion recognition based on electroencephalogram (EEG) plays an increasingly important
role in the field of brain–computer interfaces. Recently, deep learning has been widely …
role in the field of brain–computer interfaces. Recently, deep learning has been widely …
This study aimed to develop an intuitive gait-related motor imagery (MI)-based hybrid brain-
computer interface (BCI) controller for a lower-limb exoskeleton and investigate the …
computer interface (BCI) controller for a lower-limb exoskeleton and investigate the …
[HTML][HTML] MEDUSA©: A novel Python-based software ecosystem to accelerate brain-computer interface and cognitive neuroscience research
Background and objective: Neurotechnologies have great potential to transform our society
in ways that are yet to be uncovered. The rate of development in this field has increased …
in ways that are yet to be uncovered. The rate of development in this field has increased …
A temporal dependency learning CNN with attention mechanism for MI-EEG decoding
Deep learning methods have been widely explored in motor imagery (MI)-based brain
computer interface (BCI) systems to decode electroencephalography (EEG) signals …
computer interface (BCI) systems to decode electroencephalography (EEG) signals …
Dual attention relation network with fine-tuning for few-shot EEG motor imagery classification
Recently, motor imagery (MI) electroencephalography (EEG) classification techniques using
deep learning have shown improved performance over conventional techniques. However …
deep learning have shown improved performance over conventional techniques. However …
The study of generic model set for reducing calibration time in P300-based brain–computer interface
P300-based brain-computer interfaces (BCIs) provide an additional communication channel
for individuals with communication disabilities. In general, P300-based BCIs need to be …
for individuals with communication disabilities. In general, P300-based BCIs need to be …