This repository contains the Matlab utilities as used in the Noise-Tagging project as carried out at the Radboud University, Nijmegen, the Netherlands. It involves a brain computer interface (BCI) that uses the code-modulated visual evoked potential (cVEP) to decode what a user is attending to (e.g., in a visual matrix speller) from brain activity (i.e., EEG). The Matlab code in this repository belong directly to the research article as listed below.
Please note that this repository is not maintained anymore, because the research has been continued using a Python implementation, see the PyntBCI library: https://github.com/thijor/pyntbci
- Thielen, J., van den Broek, P., Farquhar, J., & Desain, P. (2015). Broad-Band Visually Evoked Potentials: Re (con) volution in Brain-Computer Interfacing. PloS one, 10(7), e0133797. doi:10.1371/journal.pone.0133797
- Thielen, J., Marsman, P., Farquhar, J., & Desain, P. (2017). Re (con) volution: Accurate response prediction for broad-band evoked potentials-based brain computer interfaces. In Brain-Computer Interface Research (pp. 35-42). Springer, Cham.
- Desain, P. W. M., Thielen, J., van den Broek, P. L. C., & Farquhar, J. D. R. (2019). U.S. Patent No. 10,314,508. Washington, DC: U.S. Patent and Trademark Office.
Please, also see https://www.mindaffect.nl/ to "open up new dimensions of interaction" using a brain computer interface.