BRAIN Journal-Novel Detection Features for SSVEP Based BCI: Coefficient of Variation and Variation Speed-Figure 5. SSVEP detection accuracies by using PSD, CV and VS features
When the results in Figure 5 are analyzed, it is seen that CV and VS features provide detection results similar to PSD, which is a familiar feature. Considering that the chance level is 12.5% in these dataset, CV and VS can be used as discriminative features for SSVEP. Also on some subjects, like S3 on 1st and 4th datasets, and S11 on 1st, 2nd and 4th datasets, the proposed features have given clearly better detection results than PSD.