Classification toolbox for ERP and SSVEP based BCI data

The source code of the OACCA introduced in our IEEE TBME paper (10.1109/TBME.2021.3133594)

Matlab code of our IEEE TASE paper "Wong, C. M., Wang, Z., Rosa, A. C., Chen, C. P., Jung, T. P., Hu, Y., & Wan, F. (2021). Transferring subject-specific knowledge across stimulus frequencies in SSVEP-based BCIs. IEEE Transactions on Automation Science and Engineering, 18(2), 552-563."

Data mining based approach to study the effect of caffeinated coffee on SSVEP brain signals. https://doi.org/10.1016/j.compbiomed.2019.103526

Simulations of stimulus-stimulus transfer based on time-frequency-joint representation in SSVEP-based BCIs. The proposed stimulus-stimulus transfer method has been published in IEEE TBME (DOI: 10.1109/TBME.2022.3198639)

Gaze data -based epoch selection algorithm for eye tracker assisted visual evoked potential paradigm

Data and code for the metrological characterization of a low-cost wearable brain-computer interface

EEG Signal Processing project, which involves analyzing EEG signals for both ERP and SSVEP.

Processing bioelectrical signals and medical images