A New Online Event Related Potential Based Brain-Computer Interfaces Using an Ensemble Classifier

被引：0
作者：
Onishi, Akinari [1 ]
Natsume, Kiyohisa [1 ]
机构：
[1] Kyushu Inst Technol, Grad Sch Life Sci & Syst Engn, Dept Brain Sci & Engn, Wakamatsu Ku, Kitakyushu, Fukuoka 8080196, Japan
来源：
2013 6TH INTERNATIONAL IEEE/EMBS CONFERENCE ON NEURAL ENGINEERING (NER) | 2013年
关键词：
P300; SPELLER;
D O I：
暂无
中图分类号：
R318 [生物医学工程];
学科分类号：
0831 ;
摘要：
The brain computer interface (BCI) records brain signals, then translates them into commands for control devices for a better quality of life. The event related potential (ERP) has been used to drive the BCIs, but they still have room for improving its performance toward a practical use. In this study we evaluated an online ERP-based BCI system that had an ensemble classifier with overlapped partitioning and a stimulator which provided image intensifications. We also employed and compared four types of visual stimuli: a neutral, a positive, a negative and a traditional gray/white letter stimulus. As a result, ERP-based BCI system with the neutral, the positive and the negative image achieved significantly higher information transfer rate (41.0 +/- 22 bits per minute at best) than that with the conventional gray/white letter stimulus.
引用
收藏
页码：1033 / 1036
页数：4
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