A Comparison of Three Electrode Channels Selection Methods Applied to SSVEP BCI
There has been increasing interest in using steadystate visual evoked potential (SSVEP) in braincomputer interface systems (BCIs). The electrode channels usually used in SSVEP classification are Ol, O2 and Oz. However, optimal results of SSVEP recognition could not be obtained from the same electrode setting (Ol, O2 and Oz), which was caused by subject variation. In this paper, three methods (Sequential floating forward selection (SFFS), discrete particle swarm optimization (DPSO) and Fscore) were employed to select the optimal electrode channels. The electrode channels obtained by SFFS, DPSO and F-score were compared with traditional electrode channels (i.e., Ol, O2 and Oz), which are usually used in SSVEP BCI. The results show that SFFS and DPSO can obtain higher classification accuracy than traditional approach. The results also show that SFFS is superior to DPSO in terms of calculating time, and F-score is not good compared to other two methods. Channel selection can not only reduce features for data analysis but also reduce the time for channel installation.
Discrete particle swarm optimization (DPSO) Sequential floating forward selection (SFFS) F-score SSVEP electrode channels selection
Lying Meng Jing Jin Xingyu Wang
Key Laboratory of Advanced Control and Optimization for Chemical Processes, Ministry of Education,School of Information Science and Engineering, East China University of Science and Technology Shanghai, China
国际会议
上海
英文
582-585
2011-10-15（万方平台首次上网日期，不代表论文的发表时间）