【摘 要】
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Effective user training could help us to improve the discrimination performance of our intention in brain computer interface(BCI).The purpose of this study is to explore better training method to faci
【机 构】
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Shenzhen Institutes of Advanced Technology,Chinese Academy of Sciences,Shen Zhen,518055
【出 处】
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2014年上海市研究生学术论坛:生物医疗仪器
论文部分内容阅读
Effective user training could help us to improve the discrimination performance of our intention in brain computer interface(BCI).The purpose of this study is to explore better training method to facilitate the user learning process in the BCIs.In this paper,three different scenarios in 3D virtual environment are designed,including non-object-directed(NOD)scenario,static-object directed(SOD)scenario and dynamic-object-directed(DOD)scenario,and guide users to perform the correlating motor imagery(MI)based tasks.We fully compare the task classification results of these three scenarios in both single-subject paradigm and multiple-subject paradigm respectively.The results demonstrate different visual display caninfluence the user training effect.We identify both SOD and DOD scenarios provide better classification accuracy,shorten single-trial period,and need smaller training samples comparing with the NOD case.Our findings further demonstrate better classification performance can also be achieved by the multiple-subject paradigm.We believe these findings have the potential to improvethe discrimination performance of users intention for the EEG-based BCI application.
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