混合范式脑-机接口研究进展综述

传统脑-机接口(BCI)在实际应用中存在许多不足,例如指令集较小、适用人群范围小、难以实现多维度控制和异步控制等。混合范式脑-机接口(hBCI)的出现可有效解决这些问题。对基于脑电信号的hBCI、基于脑电信号和其他脑信号的hBCI以及基于多生理信号的hBCI进行综述,并分析近年来不同hBCI系统的刺激范式、控制策略、分类性能以及实际应用等。与传统BCI系统相比,hBCI系统具有更大的指令集和更高的准确率,并且由于结合了其他脑信号或生理信号,使得多维控制和异步控制更容易实现,系统实用性得到了极大的提升。最后对不同类型的hBCI系统进行了总结,阐述当前hBCI存在的问题及其未来的发展前景。

A Review of Research Progress of Hybrid Brain-Computer Interface

Traditional brain-computerinterface (BCI) has many shortcomings in practical applications, such as a small instruction set, a small range of people, hard to achieve multi-dimensional control and asynchronous control. Hybrid Brain-Computer Interface (hBCI) can effectively solve these problems. In this paper, three common types of hBCI were reviewed, including hBCI based on EEG signals, hBCI based on EEG signals and other brain signals, and hBCI based on multiple physiological signals. In addition, this paper focused on the research status of hBCI systems and analyzed the stimulus paradigm, control strategy, classification performance, and practical application. The analysis results showed that compared with the traditional BCI system, the hBCI system has a much larger instruction set and higher accuracy. Moreover, due to the combination of other brain signals or physiological signals, hBCI is easier to realize multi-dimensional control and asynchronous control and has achieved rapid development in the utility performance of the system. Finally, this paper summarized different types of hBCI systems and proposed existing problems and future development prospects of hBCI.