Area of research
Cognitive Neuroscience · Signal Processing
Research interest
Research interests include Computer science, Brain–computer interface, Pattern recognition (psychology), Artificial intelligence, Motor imagery, and Canonical correlation.
SMANet: A Model Combining SincNet, Multi-Branch Spatial—Temporal CNN, and Attention Mechanism for Motor Imagery BCI
Enhancing the performance of SSVEP-based BCIs by combining task-related component analysis and deep neural network
A deep learning model combining convolutional neural networks and a selective kernel mechanism for SSVEP-Based BCIs
Combing Multiple Visual Stimuli to Enhance the Performance of VEP-Based Biometrics
A Canonical Correlation Analysis-Based Transfer Learning Framework for Enhancing the Performance of SSVEP-Based BCIs
Intra- and Inter-Subject Common Spatial Pattern for Reducing Calibration Effort in MI-Based BCI
Tensor decomposition-based channel selection for motor imagery-based brain-computer interfaces
A high-frequency SSVEP-BCI system based on a 360 Hz refresh rate
Reducing calibration time in motor imagery-based BCIs by data alignment and empirical mode decomposition
Riemannian geometry-based transfer learning for reducing training time in c-VEP BCIs
Transfer Learning Based on Hybrid Riemannian and Euclidean Space Data Alignment and Subject Selection in Brain-Computer Interfaces
A Training Data-Driven Canonical Correlation Analysis Algorithm for Designing Spatial Filters to Enhance Performance of SSVEP-Based BCIs
Maximum Signal Fraction Analysis for Enhancing Signal-to-Noise Ratio of EEG Signals in SSVEP-Based BCIs
Channel selection in motor imaginary-based brain-computer interfaces: a particle swarm optimization algorithm
A Novel c-VEP BCI Paradigm for Increasing the Number of Stimulus Targets Based on Grouping Modulation With Different Codes
Transfer Learning Based on Regularized Common Spatial Patterns Using Cosine Similarities of Spatial Filters for Motor-Imagery BCI
A multi-target brain-computer interface based on code modulated visual evoked potentials
Electrode channel selection based on backtracking search optimization in motor imagery brain–computer interfaces
Stimulus Specificity of Brain-Computer Interfaces Based on Code Modulation Visual Evoked Potentials
Grouping modulation with different codes for improving performance in cVEP‐based brain–computer interfaces
Binary particle swarm optimization for frequency band selection in motor imagery based brain-computer interfaces