This is the official implementation for "OS-SSVEP: One-shot SSVEP classification". This study addresses the significant challenge of developing efficient decoding algorithms for classifying steady-state visual evoked potentials (SSVEPs) in scenarios characterized by extreme scarcity of calibration data, where only one calibration is available for each stimulus target. Please kindly cite our paper if you use our code.
@article{deng2024ssvep, title={OS-SSVEP: One-shot SSVEP classification}, author={Deng, Yang and Ji, Zhiwei and Wang, Yijun and Zhou, S Kevin}, journal={Neural Networks}, pages={106734}, year={2024}, publisher={Elsevier} }