EEG Cortical Source Feature based Hand Kinematics Decoding using Residual CNN-LSTM Neural Network
Motor kinematics decoding (MKD) using brain signal is essential to develop Brain-computer
interface (BCI) system for rehabilitation or prosthesis devices. Surface …
interface (BCI) system for rehabilitation or prosthesis devices. Surface …
On-device implementation for deep-learning-based cognitive activity prediction
Cognitive activity prediction (CAP) from electroencephalogram (EEG) signals is
progressively utilized in the field of brain–computer interface (BCI) and mental health …
progressively utilized in the field of brain–computer interface (BCI) and mental health …
EEG source imaging of hand movement-related areas: an evaluation of the reconstruction and classification accuracy with optimized channels
The hand motor activity can be identified and converted into commands for controlling
machines through a brain-computer interface (BCI) system. Electroencephalography (EEG) …
machines through a brain-computer interface (BCI) system. Electroencephalography (EEG) …
Deep-learning-based motor imagery EEG classification by exploiting the functional connectivity of cortical source imaging
Motor imagery (MI) is a commonly used brain–computer interface paradigm, and decoding
the MI-EEG signals has been an active research area in recent years. The existing methods …
the MI-EEG signals has been an active research area in recent years. The existing methods …
Advancing Brain-Computer Interface System Performance in Hand Trajectory Estimation with NeuroKinect
S Pancholi, A Giri - arXiv preprint arXiv:2308.08654, 2023 - arxiv.org
Brain-computer interface (BCI) technology enables direct communication between the brain
and external devices, allowing individuals to control their environment using brain signals …
and external devices, allowing individuals to control their environment using brain signals …
EEG source imaging of hand movement-related areas: An evaluation of the reconstruction accuracy with optimized channels
The hand motor activity can be identified and converted into commands for controlling
machines through a brain-computer-interface (BCI) system. Electroencephalography (EEG) …
machines through a brain-computer-interface (BCI) system. Electroencephalography (EEG) …
Two-Step Optimization: Selecting the Optimal Channel Placement and Brain Regions for Motor Imagery Classification with Source Imaging
VE Naas - 2024 - ntnuopen.ntnu.no
This thesis aims to address a practical question: How many Electroencephalography (EEG)
electrodes are necessary to achieve good classification with Electrophysiological Source …
electrodes are necessary to achieve good classification with Electrophysiological Source …
[PDF][PDF] Decoding of Hand Movement Intention
VE Naas - 2023 - researchgate.net
ABSTRACT Brain-Computer Interfaces (BCIs) utilizing Electroencephalography (EEG)
signals hold promise for enhancing the lives of individuals with severe motor disorders. This …
signals hold promise for enhancing the lives of individuals with severe motor disorders. This …
[PDF][PDF] Data Collection for an Electroencephalogram based Brain Computer Interface
A Shenoy, N van Duivendijk - 2024 - repository.tudelft.nl
This thesis paper will be centered around the design and creation of a Brain Computer
Interface (BCI) that is controlled through electroencephalogram (EEG) signals based on a …
Interface (BCI) that is controlled through electroencephalogram (EEG) signals based on a …
[PDF][PDF] EEG Source Imaging Enhances Motor Imagery Classification
Brain-computer Interfaces (BCIs) have been developed towards enhancing communication
and control in individuals with motor disabilities and assist in motor rehabilitation, where …
and control in individuals with motor disabilities and assist in motor rehabilitation, where …