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Deep learning in motor imagery EEG signal decoding: A Systematic Review
Thanks to the fast evolution of electroencephalography (EEG)-based brain-computer
interfaces (BCIs) and computing technologies, as well as the availability of large EEG …
interfaces (BCIs) and computing technologies, as well as the availability of large EEG …
Mental imagery classification using one-dimensional convolutional neural network for target selection in single-channel BCI-controlled mobile robot
This paper introduces the use of the one-dimensional convolutional neural network (1D-
CNN) for end-to-end EEG decoding with application towards a BCI system with a shared …
CNN) for end-to-end EEG decoding with application towards a BCI system with a shared …
Hybrid brain-computer interface with motor imagery and error-related brain activity
Objective. Brain-computer interface (BCI) systems read and interpret brain activity directly
from the brain. They can provide a means of communication or locomotion for patients …
from the brain. They can provide a means of communication or locomotion for patients …
Spectrally adaptive common spatial patterns
The method of Common Spatial Patterns (CSP) is widely used for feature extraction of
electroencephalography (EEG) data, such as in motor imagery brain-computer interface …
electroencephalography (EEG) data, such as in motor imagery brain-computer interface …
A Convolutional Network Adaptation for Cortical Classification During Mobile Brain Imaging
Deep neural networks (DNN) have become increasingly utilized in brain-computer interface
(BCI) technologies with the outset goal of classifying human physiological signals in …
(BCI) technologies with the outset goal of classifying human physiological signals in …
Perception estimation and torque control for hand prostheses using EEG and EMG signals
N Karakullukcu - 2024 - acikerisim.agu.edu.tr
Upper extremity prostheses vary based on patients' articulation levels and movement
methods. They can be cosmetic, operate mechanically with shoulder movement, or be …
methods. They can be cosmetic, operate mechanically with shoulder movement, or be …
[PDF][PDF] Compact and interpretable convolutional neural network architecture for electroencephalogram based motor imagery decoding
TA IZZUDDIN - 2022 - eprints.utm.my
Recently, due to the popularity of deep learning, the applicability of deep Neural Networks
(DNN) algorithms such as the convolutional neural networks (CNN) has been explored in …
(DNN) algorithms such as the convolutional neural networks (CNN) has been explored in …
[PDF][PDF] Федеральное государственное бюджетное учреждение науки Институт общей физики им. АМ Прохорова Российской академии наук
АА Ушаков - Москва, 2019 - diss.gpi.ru
Под терагерцевым (ТГц) понимают электромагнитное излучение в диапазоне частот
0.1–10 ТГц (или в диапазоне длин волн 3 мм–30 мкм), которое располагается между …
0.1–10 ТГц (или в диапазоне длин волн 3 мм–30 мкм), которое располагается между …