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Sensors | Free Full-Text | Multilayer Network Approach in EEG Motor Imagery with an Adaptive Threshold
Sensors | Free Full-Text | Multilayer Network Approach in EEG Motor Imagery with an Adaptive Threshold

EEG dataset of 7-day Motor Imagery BCI | IEEE DataPort
EEG dataset of 7-day Motor Imagery BCI | IEEE DataPort

New insights in motor imagery from real-time EEG feedback during fMRI
New insights in motor imagery from real-time EEG feedback during fMRI

EEG sensorimotor rhythms' variation and functional connectivity measures during motor imagery: linear relations and classification approaches [PeerJ]
EEG sensorimotor rhythms' variation and functional connectivity measures during motor imagery: linear relations and classification approaches [PeerJ]

Precise estimation of human corticospinal excitability associated with the levels of motor imagery-related EEG desynchronization extracted by a locked-in amplifier algorithm | Journal of NeuroEngineering and Rehabilitation | Full Text
Precise estimation of human corticospinal excitability associated with the levels of motor imagery-related EEG desynchronization extracted by a locked-in amplifier algorithm | Journal of NeuroEngineering and Rehabilitation | Full Text

Event-Related Desynchronization Induced by Tactile Imagery: an EEG Study | eNeuro
Event-Related Desynchronization Induced by Tactile Imagery: an EEG Study | eNeuro

Illustration of the SBELM-based model for classification of motor... | Download Scientific Diagram
Illustration of the SBELM-based model for classification of motor... | Download Scientific Diagram

GitHub - SuperBruceJia/EEG-Motor-Imagery-Classification-CNNs-TensorFlow: EEG Motor Imagery Tasks Classification (by Channels) via Convolutional Neural Networks (CNNs) based on TensorFlow
GitHub - SuperBruceJia/EEG-Motor-Imagery-Classification-CNNs-TensorFlow: EEG Motor Imagery Tasks Classification (by Channels) via Convolutional Neural Networks (CNNs) based on TensorFlow

Diagnostics | Free Full-Text | KCS-FCnet: Kernel Cross-Spectral Functional Connectivity Network for EEG-Based Motor Imagery Classification
Diagnostics | Free Full-Text | KCS-FCnet: Kernel Cross-Spectral Functional Connectivity Network for EEG-Based Motor Imagery Classification

Frontiers | Multi-Hierarchical Fusion to Capture the Latent Invariance for Calibration-Free Brain-Computer Interfaces
Frontiers | Multi-Hierarchical Fusion to Capture the Latent Invariance for Calibration-Free Brain-Computer Interfaces

An EEG Brain-Computer Interface to Classify Motor Imagery Signals | SpringerLink
An EEG Brain-Computer Interface to Classify Motor Imagery Signals | SpringerLink

Multi-channel EEG recording during motor imagery of different joints from the same limb | Scientific Data
Multi-channel EEG recording during motor imagery of different joints from the same limb | Scientific Data

Motor imagery and EEG-based control of spelling devices and neuroprostheses - ScienceDirect
Motor imagery and EEG-based control of spelling devices and neuroprostheses - ScienceDirect

Improving the Performance of an EEG-Based Motor Imagery Brain Computer Interface Using Task Evoked Changes in Pupil Diameter | PLOS ONE
Improving the Performance of an EEG-Based Motor Imagery Brain Computer Interface Using Task Evoked Changes in Pupil Diameter | PLOS ONE

EEG Spatial patterns and frequency bands used to classify motor imagery... | Download Scientific Diagram
EEG Spatial patterns and frequency bands used to classify motor imagery... | Download Scientific Diagram

Author Spotlight: Using Motor Imagery Brain-Computer Interface to Improve Motor and Cognitive Function in Stroke Patients
Author Spotlight: Using Motor Imagery Brain-Computer Interface to Improve Motor and Cognitive Function in Stroke Patients

Brain Sciences | Free Full-Text | Effects of Motor Imagery Tasks on Brain Functional Networks Based on EEG Mu/Beta Rhythm
Brain Sciences | Free Full-Text | Effects of Motor Imagery Tasks on Brain Functional Networks Based on EEG Mu/Beta Rhythm

Motor Imagery - an overview | ScienceDirect Topics
Motor Imagery - an overview | ScienceDirect Topics

Six classes of motor imagery EEG signals in the upper limb | IEEE DataPort
Six classes of motor imagery EEG signals in the upper limb | IEEE DataPort

New insights in motor imagery from real-time EEG feedback during fMRI
New insights in motor imagery from real-time EEG feedback during fMRI

Frontiers | EEG-Based BCI Control Schemes for Lower-Limb Assistive-Robots
Frontiers | EEG-Based BCI Control Schemes for Lower-Limb Assistive-Robots

Integrating simultaneous motor imagery and spatial attention for EEG-BCI control | bioRxiv
Integrating simultaneous motor imagery and spatial attention for EEG-BCI control | bioRxiv

A large electroencephalographic motor imagery dataset for electroencephalographic brain computer interfaces | Scientific Data
A large electroencephalographic motor imagery dataset for electroencephalographic brain computer interfaces | Scientific Data

Figure 3 from Detection of knee motor imagery by Mu ERD/ERS quantification for BCI based neurorehabilitation applications | Semantic Scholar
Figure 3 from Detection of knee motor imagery by Mu ERD/ERS quantification for BCI based neurorehabilitation applications | Semantic Scholar

Dynamic Classification of Time-embedded EEG with Sequential Hypothesis Testing (SHT) for Brain-Computer Interface | Weixuan 'Vincent' Chen
Dynamic Classification of Time-embedded EEG with Sequential Hypothesis Testing (SHT) for Brain-Computer Interface | Weixuan 'Vincent' Chen

Figure 2 from Motor Imagery EEG Signal Processing and Classification Using Machine Learning Approach | Semantic Scholar
Figure 2 from Motor Imagery EEG Signal Processing and Classification Using Machine Learning Approach | Semantic Scholar

Translation of EEG Spatial Filters from Resting to Motor Imagery Using Independent Component Analysis | PLOS ONE
Translation of EEG Spatial Filters from Resting to Motor Imagery Using Independent Component Analysis | PLOS ONE

Hand Motor Imagery Classification Using Effective Connectivity and Hierarchical Machine Learning in EEG Signals
Hand Motor Imagery Classification Using Effective Connectivity and Hierarchical Machine Learning in EEG Signals