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| Parameter Optimization in Face-Based P300 Speller System |
| Sun Hongyan, Jin Jing*, Zhang Yu, Wang Bei ,Wang Xingyu |
| School of Information Science and Technology, East China University of Science and Technology, Shanghai 200237, China |
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Abstract The P300 based BCI is often used in speller system, because of its high accuracy and information transfer rate. Previous studies showed that face stimulus could induce recognizable event related potentials, which improve the performance of a P300 speller system. However, the form of face stimulus presentation also directly affects the system′s performance. The experiments we executed were under three different parameters: stimulus onset asynchrony (SOA) (130ms vs 200ms), the size of screen (15.6inch vs 24inch) and image pixels (50×69 vs 80×110), and 10 healthy subjects were invited to participate in this experiment. The results showed that enlarging the three parameters all improved the per-trial classification accuracy during the offline training. However, in the process of online testing, only the paradigm with 200 ms stimulus intervals achieved significantly higher online classification accuracy than that with 130 ms stimulus intervals (90%±7% vs 75%±13%). Besides, the three paradigms’ parameter adjustments have different influences on the amplitude of ERP, such as N200, P300, N400, et al. In the practical usage of P300 speller system, parameter optimization should be taken into consideration to improve the system′s performance.
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Received: 28 March 2017
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