Zhou Huilin, Xu Jialin, Shi Changcheng, Zuo Guokun
Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo, Zhejiang 315201, P.R.China;University of Chinese Academy of Sciences, Beijing 100049, P.R.China.
Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo, Zhejiang 315201, P.R.China.
Sheng Wu Yi Xue Gong Cheng Xue Za Zhi. 2018 Oct 25;35(5):799-804. doi: 10.7507/1001-5515.201711013.
Brain-computer interface (BCI) technology enable humans to interact with external devices by decoding their brain signals. Despite it has made some significant breakthroughs in recent years, there are still many obstacles in its applications and extensions. The current used BCI control signals are generally derived from the brain areas involved in primary sensory- or motor-related processing. However, these signals only reflect a limited range of limb movement intention. Therefore, additional sources of brain signals for controlling BCI systems need to be explored. Brain signals derived from the cognitive brain areas are more intuitive and effective. These signals can be used for expand the brain signal sources as a new approach. This paper reviewed the research status of cognitive BCI based on the single brain area and multiple hybrid brain areas, and summarized its applications in the rehabilitation medicine. It's believed that cognitive BCI technologies would become a possible breakthrough for future BCI rehabilitation applications.
脑机接口（BCI）技术使人类能够通过解码大脑信号与外部设备进行交互。尽管近年来它取得了一些重大突破，但其应用和扩展仍存在许多障碍。当前使用的BCI控制信号通常来自参与初级感觉或运动相关处理的脑区。然而，这些信号仅反映了有限范围的肢体运动意图。因此，需要探索用于控制BCI系统的其他脑信号源。源自认知脑区的脑信号更直观、有效。这些信号可作为一种新方法用于扩展脑信号源。本文综述了基于单脑区和多混合脑区的认知BCI的研究现状，并总结了其在康复医学中的应用。人们认为，认知BCI技术将成为未来BCI康复应用的一个可能突破点。
