Code to accompany our International Joint Conference on Neural Networks (IJCNN) paper entitled - Simulating Brain Signals: Creating Synthetic EEG Data via Neural-Based Generative Models for Improved SSVEP Classification
Python package for SSVEP datasets and algorithms. Corresponding paper has been accepted by IEEE TNSRE (DOI: 10.1109/TNSRE.2024.3424410)
Code to accompany our International Conference on Pattern Recognition (ICPR) paper entitled - Leveraging Synthetic Subject Invariant EEG Signals for Zero Calibration BCI.
Using multi-task learning to capture signals simultaneously from the fovea efficiently and the neighboring targets in the peripheral vision generate a visual response map. A calibration-free user-independent solution, desirable for clinical diagnostics. A stepping stone for an objective assessment of glaucoma patients’ visual field.
SSVEP Brain Computer Interface - Example code for real-time detection of SSVEP using the Canonical Correlation Analysis (CCA) code in real-time. Implemented using OpenViBE and Python
uniBrain Speller: A one-stop, user-friendly, open-source brain-computer interface speller software developed by Prof. Gao Xiaorong's team at Tsinghua University, China, designed for various users including patients, researchers, and practitioners.
Code to accompany our International Conference on Robotics and Automation (ICRA) paper entitled - Using variable natural environment brain-computer interface stimuli for real-time humanoid robot navigation.
Code to accompany our 2018 IEEE International Conference on Systems, Man, and Cybernetics (SMC) paper entitled - On the classification of SSVEP-based dry-EEG signals via convolutional neural networks.
Neuroexon presents a hybrid-BCI system that utilizes motor imagery (MI) and steady-state visual-evoked potential (SSVEP) to control a one degree of freedom arm exoskeleton which provides the user with haptic feedback.
Deep Learning toolbox for EEG based Brain-Computer Interface signals decoding and benchmarking
Direct ITR optimisation for SSVEP-based BCI
Implementation of InceptionResNet for SSVEP-based Brain-Computer Interface (BCI)
Information Bottleneck as Optimisation Method for SSVEP-Based BCI
Repository for the I-VEP BCI paradigm
Code for fitting EEG data with Wishart and t-Wishart distributions
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