摘要
为了准确地分析脑电波信号受运动训练的影响,需要研究运动训练对脑电波信号的影响分析方法.采用基于时-空-频联合选择与相关向量机的运动想象脑电信号分析算法分析运动训练对脑电波信号的影响时,得到的分析结果与实际结果不符,分析所用的时间较长,存在准确率低和效率低的问题.提出一种运动训练对脑电波信号的影响建模分析方法,采用盲源分离方法对脑电波信号进行预处理,去除脑电波信号中存在的伪迹信号;结合空间模式滤波算法和Hilbert变化方法提取盲源处理后脑电波信号受运动训练影响的变化特征,建立运动训练对脑电波信号的影响模型,分析运动训练对脑电波信号的影响.实验结果表明,测试结果与影响模型得到的结果一致,验证所提方法的准确率高、效率高.
In order to accurately analyze the influence of exercise training on EEG signals,it is necessary to study the influence of exercise training on EEG signals.When analyzing the influence of exercise training on EEG signals by using the method of time-space-frequency joint selection and correlation vector machine,the results of analysis are not consistent with the actual results.The analysis takes a long time,and has the problems of low accuracy and efficiency.In this paper,a method of modeling and analyzing the influence of exercise training on EEG signals is proposed.Blind source separation is used to preprocess EEG signals and remove the artifacts in EEG signals.Blind source processing is combined with spatial mode filtering and Hilbert change to extract the EEG signals affected by exercise training.Change characteristics,establish the influence model of exercise training on EEG signal,and analyze the influence of exercise training on EEG signal.The experimental results showed that the test results are consistent with those of the impact model,and the accuracy and efficiency of the proposed method are verified.
作者
张晓亮
ZHANG Xiaoliang(Shanxi Management Vocational College,Linfen 041051,China)
出处
《周口师范学院学报》
CAS
2019年第2期85-89,共5页
Journal of Zhoukou Normal University