LASSO based stimulus frequency recognition model for SSVEP BCIs

• Published in: Biomedical signal processing and control Vol. 7; no. 2; pp. 104 - 111
• Main Authors: Zhang, Yu, Jin, Jing, Qing, Xiangyun, Wang, Bei, Wang, Xingyu
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.03.2012
• Subjects: Brain–computer interfaces (BCIs); Electroencephalogram (EEG); Least absolute shrinkage and selection operator (LASSO); Steady-state visual evoked potential (SSVEP); Time window (TW); Brain–computer interfaces (BCIs); Steady-state visual evoked potential (SSVEP); Electroencephalogram (EEG); Least absolute shrinkage and selection operator (LASSO); Time window (TW)

Steady-state visual evoked potential (SSVEP) has been increasingly used for the study of brain–computer interface (BCI). How to recognize SSVEP with shorter time and lower error rate is one of the key points to develop a more efficient SSVEP-based BCI. To achieve this goal, we make use of the sparsi...