This paper introduces novel detection features for the steady-state visually evoked potential (SSVEP) based brain computer interfaces. The coefficient of variation and variation speed features were developed using the stability of SSVEP response. The developed features were tested on 13 subjects. On this dataset, for which the chance level is 12.5%, about 70% detection accuracy was obtained. Based on these results, it is considered that the coefficient of variation and the variation speed can be used as discriminative features for SSVEP. By using familiar SSVEP features and developed features together, higher SSVEP detection accuracy can be obtained. By this procedure the performance of single channel SSVEP based BCI systems can be improved.