An Improved Composite Multiscale Fuzzy Entropy for Feature Extraction of MI-EEG

Motor Imagery Electroencephalography (MI-EEG) has shown good prospects in neurorehabilitation, and the entropy-based nonlinear dynamic methods have been successfully applied to feature extraction of MI-EEG. Especially based on Multiscale Fuzzy Entropy (MFE), the fuzzy entropies of the τ coarse-grained sequences in τ scale are calculated and averaged to develop the Composite MFE (CMFE) with more feature information. However, the coarse-grained process fails to match the nonstationary characteristic of MI-EEG by a mean filtering algorithm. In this paper, CMFE is improved by assigning the different weight factors to the different sample points in the coarse-grained process, i.e., using the weighted mean filters instead of the original mean filters, which is conductive to signal filtering and feature extraction, and the resulting personalized Weighted CMFE (WCMFE) is more suitable to represent the nonstationary MI-EEG for different subjects. All the WCMFEs of multi-channel MI-EEG are fused in serial to construct the feature vector, which is evaluated by a back-propagation neural network. Based on a public dataset, extensive experiments are conducted, yielding a relatively higher classification accuracy by WCMFE, and the statistical significance is examined by two-sample t-test. The results suggest that WCMFE is superior to the other entropy-based and traditional feature extraction methods.     

基于非线性参数的意识任务分类

研究了非线性参数作为脑电（EEG）信号特征时对意识任务分类的作用，使用的3种非线性参数特征为最大Lyapunov指数、轨道平均周期和轨道平均初始距离，分类方法为Fisher线性判别式．对4个实验对象共60个任务对进行了分类处理．使用3种参数在2s数据段上取得的平均分类精度分别为82．3％、90．7％和93．3％．在较短（1s）的数据段上，应用轨道平均初始距离参数进行分类取得了平均为90．8％的正确率，分类精度接近于Anderson取得的实验结果．轨道平均周期和轨道平均初始距离算法具有较小的运算量，能够应用于在线系统．     

基于脑电Alpha波的脑-机接口控制实验

对脑电alpha波阻断现象的识别提取与家用电器遥控装置的结合进行了研究，以探索实时脑机接口（brain-computer interface，BCI）系统的可行性．对5～12名受试者进行睁闭眼实验并记录其动态脑电数据，提取alpha波阻断现象发生过程的关键参数．在实时操作平台上对受试者进行4组遥控器按键操作的组合实验，以考察系统的响应速度与指令传递的准确率．总结出了Alpha波阻断现象对应的阈值电压经验计算公式，并建立了以最大噪声背景电平作为甄别开关动作真伪的判据原则．结果显示该系统具有较高的控制成功率和稳定性，表明实时脑机接口系统具有潜在的临床应用价值与研究前景.     

基于机器学习的跨患者癫痫自动检测算法

针对目前癫痫自动检测算法多集中于为单个患者建立检测模型,泛化能力较弱的问题,提出一种基于机器学习的跨患者癫痫自动检测算法.该算法使用多个癫痫患者的脑电数据,先对数据进行预处理后分析脑电数据间存在的特征,再对特征进行筛选,训练出一个跨患者的癫痫自动检测模型.该算法不需为每个患者建立单独的检测模型,实现了仅使用一个检测模型...     

脑电信号的现代谱分析技术

脑电信号是非平稳随机信号，它的频域特性的正确表达及精度，相位信息的提取，瞬态波形分析是当前ＥＥＧ信号处理研究中的３个热点问题，本针对以上问题讨论了谱参量分析，双谱分析以及时间－频率域分析的原理，方法，并给出一些ＥＥＧ信号处理的研究结果。     

基于脑区社团结构的恐高程度识别模型

高层建筑拔地而起,客观的恐高检测手段是高空作业行业规范化的关键一步.本文结合虚拟现实技术设计高空暴露实验,深入研究了恐高反应的大脑神经机制,提出使用脑功能网络检测恐高程度.通过对比不同恐高程度脑功能网络的基本拓扑特征,使用阈值化处理找出与恐高程度关系密切的脑区.根据脑区划分社团结构,构建恐高程度识别模型.结果表明:恐高...     

Effects of Thai Local Ingredient Odorants,Litsea cubeba and Garlic Essential Oils,on Brainwaves and Moods

The functional food market is growing with a compound annual growth rate of 7.9%. Thai food recipes use several kinds of herbs. Lemongrass, garlic, and turmeric are ingredients used in Thai curry paste. Essential oils released in the preparation step create the flavor and fragrance of the famous tom yum and massaman dishes. While the biological activities of these ingredients have been investigated, including the antioxidant, anti-inflammatory, and antimicrobial activities, there is still a lack of understanding regarding the responses to the essential oils of these plants. To investigate the effects of essential oil inhalation on the brain and mood responses, electroencephalography was carried out during the non-task resting state, and self-assessment of the mood state was performed. The essential oils were prepared in several dilutions in the range of the supra-threshold level. The results show that Litsea cubeba oil inhalation showed a sedative effect, observed from alpha and beta wave power reductions. The frontal and temporal regions of the brain were involved in the wave alterations. Garlic oil increased the alpha wave power at lower concentrations; however, a sedative effect was also observed at higher concentrations. Lower dilution oil induced changes in the fast alpha activity in the frontal region. The alpha and beta wave powers were decreased with higher dilution oils, particularly in the temporal, parietal, and occipital regions. Both Litsea cubeba and turmeric oils resulted in better positive moods than garlic oil. Garlic oil caused more negative moods than the others. The psychophysiological activities and the related brain functions require further investigation. The knowledge obtained from this study may be used to design functional food products.     

脑机接口技术研究方法

脑机接口（BCI）是一种基于脑电信号实现人脑与计算机或其他电子设备通讯和控制的系统，它不依赖人体的外周神经神经系统及肌肉组织，是一种新的人机接口方式，在康复医学和控制等领域有应用前景，近年来，脑机接口技术发展迅速。概述了采用事件相关电位P300、稳态视觉诱发电位（SSVEP）、事件相关同步或去同步9ERS／ERD）皮层慢电位（SCP）、自发EEG信号、植入电极等实现脑机接口技术的研究方法，讨论和比较了各种研究方法的特点和局限，介绍了脑机接口的发展现状和存在的问题，并对其应用前景进行了展望。     

脑电图监测对额叶癫痫发作性患者的早期诊断及术中辅助定位价值研究

癫痫的早期诊断对预后恢复具有重要意义,因此本文对脑电图在癫痫患者术前诊断和辅助手术治疗方面的应用价值进行了综合性探究.选择经临床确诊为额叶癫痫的60例患者作为研究对象进行回顾性研究,术前、术后分别通过头颅核磁共振和脑电图对患者进行检查,比较两种检测方法的灵敏度、特异度和准确率.经研究发现,脑电图与MRI检查相比,其诊断...     

柔性衬底MEMS技术制备脑电图干电极阵列研究

设计了一种新型的脑电图干电极,主要用于采集脑电信号以进行基于脑电图的警觉度分析,替代传统的湿电极.采用柔性衬底微电子机械系统(MEMS)加工技术,在柔性衬底上制备出具有化学稳定性与生物相容性的微针状干电极阵列.通过铜牺牲层实现干电极微针的悬臂梁结构,利用聚二甲基硅氧烷(PDMS)剥离层实现器件从玻璃基底的完全释放,并经平面电极的多层组装实现了立体电极阵列.实验中干电极以聚酰亚胺作为柔性衬底,其针端及导线部分材料为镍,针端部分表面镀金.采用Neuroscan的脑电信号采集放大器对干电极性能进行了测试,测得阻抗约为10 kΩ,其时域和频域信号与传统湿电极基本一致.所制备的干电极成品率高、尺寸小、屏蔽佳、装配简单、可靠性好、机械强度大,符合快速、无痛的脑电信号采集要求.