摘要
通过分析脑电信号特征变化情况,探讨神经反馈(NFB)训练对轻度认知障碍(MCI)患者认知能力的改善作用。使用NFB训练作为干预方法,对40例MCI患者进行两个周期共10 d的训练。提出了一种使数据更平稳、去除扰动的改进模糊熵,并以复杂度、近似熵及相干性作为脑电分析方法,对比其在训练前后的变化情况,同时辅助以阿尔茨海默病评定量表认知分量表(ADAS-Cog)。训练后,实验组脑电(EEG)信号复杂度、近似熵及改进模糊熵特征量均增加,前后差异均具有统计学意义(P<0.05),改进模糊熵增量最为明显。顶区、额区和颞区半球间的脑电相干性值增量最大;与认知功能联系紧密的gamma、beta、alpha和theta频带的脑电相干性在训练后增量明显。ADAS-Cog得分普遍降低,表明认知能力提高。本研究证明了NFB训练对MCI患者的认知功能改善作用,及其作为MCI人群干预方法的可行性。
The changes of electroencephalogram(EEG)characteristics are analyzed to explore the effect of neurofeedback(NFB)training on mild cognitive impairment(MCI)patients’cognitive ability.NFB training is utilized in 40 MCI patients in order to explore its role in cognitive function for 10 days in two cycles.An improved fuzzy entropy that removes noise and smoothes the data is proposed to analyze EEG,accompanied by complexity,approximate entropy and hemispherical coherence,and supported by Alzheimer’s disease assessment scale-cognitive subscale(ADAS-Cog).After training,the complexity,approximate entropy and improved fuzzy entropy are statistically significant(P<0.05),and improved fuzzy entropy has the most obvious change.The increment values of interhemispheric EEG coherence in the parietal,frontal,and temporal regions are the largest;coherence of the gamma,beta,alpha,and theta bands,which are closely related to cognitive function,increases significantly after training.On average,ADAS-Cog scores decrease,which means cognitive function has improved.It’s proved that NFB training can improve the cognitive function and demonstrates the feasibility of NFB as an intervention method for MCI patients.
作者
李昕
苏芮
史春燕
张洁
李向东
丁欣悦
Li Xin;Su Rui;Shi Chunyan;Zhang Jie;Li Xiangdong;Ding Xinyue(Institute of Biomedical Engineering, College of Electrical Engineering, Yanshan University, Qinhuangdao 066004;Measurement Technology and Instrumentation Key Laboratory of Hebei Province, Qinhuangdao 066004;Huisianpu Medical Instruments Co. Ltd., Qinhuangdao 066000)
出处
《高技术通讯》
EI
CAS
北大核心
2020年第12期1292-1299,共8页
Chinese High Technology Letters
基金
中国博士后科学基金(2014M550582)
河北省自然科学基金(F2019203515)资助项目。