Research Advancements on the Variation and Prediction of Brain Control Performance for Brain-Computer Interfaces (BCIs)
Zheng Yufu1, Xu Minpeng1,2#*, Ming Dong1,2#
1School of Precision Instrument and Opto-Electronics, Tianjin University, Tianjin 30072, China; 2Institute of Medical Engineering and Translational Medicine, Tianjin University, Tianjin 30072, China
Abstract：Brain-computer interface (BCI) technology has attracted significant attention over recent decades, and has made remarkable progress. However, Brain control performance variations across and even within subjects severely degrade the reliability of BCI systems, which has become one of the most important challenges in the real-life application of brain-computer interfaces (BCIs). Understanding the underlying causes is essential to improve the stability of BCI systems, which could be approached by predicting BCI performance. Reliable prediction on individual’s ability to control BCIs can distinguish BCI illiteracy and can help eliminate the performance differences among users; while reliable prediction across trials for the same subject can help improve the whole BCI performance. This paper reviewed recent studies on the prediction of BCI performance, which laid emphasis on the BCI illiteracy and the causes of the BCI performance variation. It also provided some possible directions for future studies.
郑玉甫, 许敏鹏, 明东. 脑-机接口操控效果差异及其预测研究综述[J]. 中国生物医学工程学报, 2018, 37(6): 749-755.
Zheng Yufu, Xu Minpeng, Ming Dong. Research Advancements on the Variation and Prediction of Brain Control Performance for Brain-Computer Interfaces (BCIs). Chinese Journal of Biomedical Engineering, 2018, 37(6): 749-755.
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