Laboratory for Neural Interface and Brain Computer Interface, Engineering Research Center of AI & Robotics, Ministry of Education, Shanghai Engineering Research Center of AI & Robotics, MOE Frontiers Center for Brain Science, State Key Laboratory of Medical Neurobiology, Institute of AI and Robotics, Academy for Engineering and Technology, FUDAN University, Shanghai 200433, China.
Ji Hua Laboratory, Foshan 528200, Guangdong, China.
Comput Intell Neurosci. 2022 Mar 10;2022:8112375. doi: 10.1155/2022/8112375. eCollection 2022.
. Stroke patients are usually accompanied by motor dysfunction, which greatly affects daily life. Electroacupuncture is a kind of nondrug therapy that can effectively improve motor function. However, the effect of electroacupuncture is hard to be measured immediately in clinic. This paper is aimed to reveal the instant changes in brain activity of three groups of stroke patients before, during, and after the electroacupuncture treatment by the EEG analysis in the alpha band and beta band. Seven different functional connectivity indicators including Pearson correlation coefficient, spectral coherence, mutual information, phase locking value, phase lag index, partial directed coherence, and directed transfer function were used to build the BCI-based brain network in stroke patients. . The results showed that the brain activity based on the alpha band of EEG decreased after the electroacupuncture treatment, while in the beta band of EEG, the brain activity decreased only in the first two groups. . This method could be used to evaluate the effect of electroacupuncture instantly and quantitatively. The study will hopefully provide some neurophysiological evidence of the relationship between changes in brain activity and the effects of electroacupuncture. The study of BCI-based brain network changes in the alpha and beta bands before, during, and after electroacupuncture in stroke patients of different periods is helpful in adjusting and selecting the electroacupuncture regimens for different patients. The trial was registered on the Chinese clinical trial registry (ChiCTR2000036959).
中风患者通常伴有运动功能障碍，这极大地影响了他们的日常生活。电针是一种非药物治疗方法，可有效改善运动功能。然而，电针的效果在临床上很难立即得到衡量。本文旨在通过 EEG 在 alpha 波段和 beta 波段分析，揭示三组中风患者在电针治疗前、中、后大脑活动的即时变化。本文使用了七种不同的功能连接指标，包括皮尔逊相关系数、谱相干性、互信息、锁相值、相位滞后指数、偏定向相干性和定向传递函数，构建了基于中风患者脑电的 BCI 脑网络。结果表明，电针治疗后脑电 alpha 波段的脑活动减少，而在 EEG 的 beta 波段，脑活动仅在前两组中减少。该方法可用于即时、定量地评估电针的效果。本研究有望为脑活动变化与电针效果之间的关系提供一些神经生理学证据。研究不同时期中风患者电针前、中、后 alpha 波段和 beta 波段的基于 BCI 的脑网络变化有助于为不同患者调整和选择电针方案。该试验在中国临床试验注册中心（ChiCTR2000036959）注册。
