频带能量与样本熵在注意力脑电信号中的对比研究

脑电波是一种复杂的生物电信号,可反应出大脑内部的活动及注意力等精神状态。基于此,论文设计了注意力相关的脑电实验,并完成了受试者脑电数据的采集,对所采集的脑电数据分别从以下两种角度进行研究:从时频分析的角度,采用db4小波基对原始脑电信号进行7层小波包分解,提取了β波/θ波能量占比作为特征量;从非线性动力学的角度,提取脑电信号的样本熵作为特征,并分别对各受试者进行注意力的分级研究。通过对比分析,结果表明两者都能从一定程度上表征注意力水平的状况,但样本熵对于多级注意力的区分度更好。     

基于多元经验模态分解-传递熵的脑肌电信号耦合分析

皮层肌肉功能耦合是大脑皮层和肌肉组织间的相互作用,脑肌电信号的多尺度耦合特征可以体现皮层-肌肉间多时空的功能联系.将多元经验模态分解(MEMD)与传递熵(TE)结合,构建出MEMD-TE模型,应用于脑、肌间耦合分析.首先对同步采集的脑电(EEG)和肌电(EMG)信号进行预处理,然后采用多元经验模态分解算法对信号进行时-频尺度化,最后计算不同尺度上的传递熵值,分析各个尺度不同耦合方向(EEG→EMG及EMG→EEG)上的非线性耦合特征.采集了10名受试者静态握力(5 kg、10 kg、20 kg)下脑、肌电信号,实验结果表明:脑电对肌电的MEMD-TE值在高频段(40 Hz~75 Hz)上高于肌电对脑电的MEMD-TE值,皮层肌肉功能耦合具有双向性,且不同方向和频段上的耦合强度有所差异,显著性校验反映了不同力度下脑电对肌电的MEMD-TE值没有显著性差别.     

基于 BCI 的虚拟现实模拟驾驶教学系统设计

为解决传统模拟驾驶过于强调正常场景的训练,缺少对意外场景下学员心理状态 的监测与协助,且无法反馈和评价驾驶心理状态等问题。以脑机交互(BCI)技术与虚拟现实(VR) 为基础开发 VR 模拟驾驶教学演示系统,利用三维动力学引擎开发了驾驶模拟操作系统,在硬 件上设计可穿戴式脑电波信号检测头盔,基于 BCI 技术实现对学员模拟驾驶大脑状态的监控与 数据评估;有突发模拟事件发生时,系统通过脑机接口技术自动制动或辅助驾驶。在完成模拟 驾驶训练的同时可以根据脑波(EEG)反馈在意外事件中给出紧急解救措施,根据 EEG 情况评估 学员的发挥以及心理素质,为虚拟驾驶等认知负荷较高的教学训练提供了更为丰富与直观沉浸 式交互操作方式,提高了该领域教学训练系统的实用性与可用性。     

基于特征融合方法的轻微认知衰退静息态脑电数据自动检测技术研究

轻微认知衰退是阿尔茨海默病的早期阶段,而利用脑电信号进行轻微认知衰退的特征提取与分类是诊断轻微认知衰退的重要方法。在基于脑电人工智能轻微认知衰退自动检测技术中,现有研究只提取脑电波信号中的某一个特征或简单地拼接多个特征,这会导致这些方法并不能较好地考虑特征之间的相关性,并且会引发维度灾难的问题;提出了一种基于卷积神经网络的轻微认知衰退静息态脑电数据自动检测算法,通过提取脑电的功率谱及脑网络特征,并通过矩阵运算的方式对这两种特征进行融合,利用卷积神经网络对融合后的特征进行分类。该方法在上海某医院采集的数据集上获得较高的准确率;此外,通过输入特征集的不同子集,该方法找到了对轻微认知衰退最有贡献的几组特征,从而还具有一定的可解释性。在本数据集上证明了功率脑网络对于轻微认知衰退自动诊断的优势。     

基于汉语音位发音想象的脑机接口研究

该文提出了一个基于汉语音位发音想象的脑机接口系统框架,使得受试者使用脑机接口系统时能更加自然和流畅。三名受试者参与了本实验研究,实验过程中受试者被要求想象四个汉语元音和四个辅音音位的发音部位及语音发音,以及一个不作想象任务的控制条件,同时记录其脑电数据。在数据处理阶段,本文对采集到的头皮脑电数据进行了频域、时域、空域分析,以提取出音位发音想象效应最优化的特征向量用于提高每两个条件间的配对分类效果。实验结果表明,音位发音想象效应的最优脑电频段为2~10Hz,时段为刺激呈现后300~500ms,头皮空间分布主要集中在感觉运动皮层区域。音位发音想象任务和控制条件相比具有较高的分类正确率,最高可达83%,为基于音位发音想象的汉语脑机接口系统研究提供了理论基础。此外,刺激材料间的Jaccard距离和分类正确率的高度相关性表明,音位发音想象任务可被视为复杂的发音器官运动想象任务,并且可由人脑感觉运动皮层区域的脑电信号来解码预测。     

基于脑电时频空多域特征融合的情感识别研究

传统基于脑电信号（electroencephalogram,EEG）的情感识别主要采用单一的脑电特征提取方法,为了充分利用EEG中蕴含的丰富信息,提出一种多域特征融合的脑电情感识别新方法。提取了EEG的时域、频域和空域特征,将三域特征进行融合作为情感识别模型的输入。首先计算不同时间窗EEG信号的alpha、beta、gamma三个频段功率谱密度,并结合脑电电极空间信息构成EEG图片,然后利用卷积神经网络（convolutional neural network,CNN）与双向长短期记忆网络（bidirectional long short-term memory network,BLSTM）构建CNN-BLSTM情感识别模型,分别对时、频、空三域特征进行学习。在SEED数据集对该方法进行验证,结果表明该方法能有效提高情感识别精度,平均识别准确率达96.25%。     

精神分裂症患者工作记忆EEG功能网络属性分析

精神分裂症与一些认知障碍如信息处理、工作记忆等联系紧密,研究工作是记忆任务中精神分裂症患者与正常人的多通道脑电在各个阶段、各个频段存在哪些显著性差异,可为精神分裂症的诊断提供依据。使用相位锁值（Phase Locking Value,PLV）来量化任意两个电极通道之间的相位同步性,构建脑功能网络的关联矩阵,计算不同稀疏度下脑网络的全局属性以及局部属性曲线下面积,在同一阶段、同一频段下对精神分裂症患者和正常人得到的属性值进行非参数检验,找出差异显著的属性及节点,将对应值作为特征训练SVM分类器,进而将精神分裂症患者和正常人分类。属性分析结果表明,工作记忆任务中[θ]和[α]频段发挥主要作用的脑区集中在右侧额叶区和枕叶区,[γ]频段相关的脑区集中在顶叶区;精神分裂症患者额叶右侧区域与枕叶区电极间[θ、][α]波相关性低于正常人,而其顶叶区电极间[γ]波的相关性高于正常人。     

基于MSE-PCA的脑电睡眠分期方法研究

针对传统的自动睡眠分期准确率不足问题,提出一种将多尺度熵(MSE)和主成分分析(PCA)联合使用的自动睡眠分期方法。以8例受试者睡眠脑电(EEG)监测数据及专家人工分期结果作为样本,首先使用MSE表征受试者脑电信号不同睡眠期的非线性动力学特征;然后使用PCA的前两个主成分向量代替MSE特征进行降维,实现降低数据冗余的同时保留绝大多数EEG非线性特征;最终将新向量的特征参数输入到反馈神经网络(BPNN)分类器中实现MSE-PCA模型的脑电睡眠状态的自动识别分类。实验结果表明,自动分期准确率可达到87.9%,kappa系数0.77,该方法能提高脑电自动睡眠分期系统的准确率和稳定性。     

基于轻音乐加音乐节拍方式的大脑双重刺激诱导方法

依据音乐旋律以及节拍对脑电波能量谱的影响,提出一种轻音乐加音乐节拍的双重刺激诱导方法。对测试者的大脑意识活动进行调节,通过分析采集到的脑电信号判断其是否能够快速进入高度放松状态。在调节阶段采用轻音乐加速度渐变和强弱顺序相反的音乐节拍声方式,使被测试者倾听5 min,并对通过EEG耳机采集的脑电信号进行分析。实验结果表明,该方法在调节持续时间约为2 min~3 min时,能够有效地促进大脑进入高度放松状态。     

脑电信号情绪识别综述

情绪识别在医疗领域和人机互动中越来越重要。当人们的情绪在外部刺激下发生变化时，人体的各种生理信号就会产生波动。脑电图（EEG）与大脑活动密切相关，因此可以通过EEG信号判断受试者的情绪变化。首先，从特点和采集、预处理、公开数据集等方面介绍了脑电情绪识别的相关理论；然后，从时域、频域和时频域特征介绍了EEG信号的特征提取；随后，对EEG信号情绪分类识别的效果进行评估；最后，总结了EEG信号情绪识别的相关工作并对未来工作进行了展望。     

Only connect: teaching, technology and telesis

Abstract This paper describes an approach to the design of interactive multimedia materials being developed in a European Community project. The developmental process is seen as a dialogue between technologists and teachers. This dialogue is often problematic because of the differences in training, experience and culture between them. Conditions needed for fruitful dialogue are described and the generic model for learning design used in the project is explained.     

European Community policy and the market

Abstract This paper starts with some reflections on the policy considerations and priorities which are shaping European Commission (EC) research programmes. Then it attempts to position the current projects which seek to capitalise on information and communications technologies for learning in relation to these priorities and the apparent realities of the marketplace. It concludes that while there are grounds to be optimistic about the contribution EC programmes can make to the efficiency and standard of education and training, they are still too technology driven.     

一种自适应子融合集成多分类器方法

融合集成方法已经广泛应用在模式识别领域,然而一些基分类器实时性能稳定性较差,导致多分类器融合性能差,针对上述问题本文提出了一种新的基于多分类器的子融合集成分类器系统。该方法考虑在度量层融合层次之上通过对各类基多分类器进行动态选择,票数最多的类别作为融合系统中对特征向量识别的类别,构成一种新的自适应子融合集成分类器方法。实验表明,该方法比传统的分类器以及分类融合方法识别准确率明显更高,具有更好的鲁棒性。     

Avoiding semantic and temporal gaps in developing software intensive systems

Development of software intensive systems (systems) in practice involves a series of self-contained phases for the lifecycle of a system. Semantic and temporal gaps, which occur among phases and among developer disciplines within and across phases, hinder the ongoing development of a system because of the interdependencies among phases and among disciplines. Such gaps are magnified among systems that are developed at different times by different development teams, which may limit reuse of artifacts of systems development and interoperability among the systems. This article discusses such gaps and a systems development process for avoiding them.     

Designing economic np control charts: A programmed simulation approach

This paper presents control charts models and the necessary simulation software for the location of economic values of the control parameters. The simulation program is written in FORTRAN, requires only 10K of main storage, and can run on most mini and micro computers. Two models are presented - one describes the process when it is operating at full capacity and the other when the process is operating under capacity. The models allow the product quality to deteriorate to a further level before an existing out-of-control state is detected, and they can also be used in situations where no prior knowledge exists of the out-of-control causes and the resulting proportion defectives.     

The development of robot art

Going through a few examples of robot artists who are recognized worldwide, we try to analyze the deepest meaning of what is called “robot art” and the related art field definition. We also try to highlight its well-marked borders, such as kinetic sculptures, kinetic art, cyber art, and cyberpunk. A brief excursion into the importance of the context, the message, and its semiotics is also provided, case by case, together with a few hints on the history of this discipline in the light of an artistic perspective. Therefore, the aim of this article is to try to summarize the main characteristics that might classify robot art as a unique and innovative discipline, and to track down some of the principles by which a robotic artifact can or cannot be considered an art piece in terms of social, cultural, and strictly artistic interest. This work was presented in part at the 13th International Symposium on Artificial Life and Robotics, Oita, Japan, January 31–February 2, 2008     

Explanation and prediction: an architecture for default and abductive reasoning

Although there are many arguments that logic is an appropriate tool for artificial intelligence, there has been a perceived problem with the monotonicity of classical logic. This paper elaborates on the idea that reasoning should be viewed as theory formation where logic tells us the consequences of our assumptions. The two activities of predicting what is expected to be true and explaining observations are considered in a simple theory formation framework. Properties of each activity are discussed, along with a number of proposals as to what should be predicted or accepted as reasonable explanations. An architecture is proposed to combine explanation and prediction into one coherent framework. Algorithms used to implement the system as well as examples from a running implementation are given.     

Three Process Perspectives: Organizations, Teams, and People

This paper provides the author's personal views and perspectives on software process improvement. Starting with his first work on technology assessment in IBM over 20 years ago, Watts Humphrey describes the process improvement work he has been directly involved in. This includes the development of the early process assessment methods, the original design of the CMM, and the introduction of the Personal Software Process (PSP)^SM and Team Software Process (TSP){^SM}. In addition to describing the original motivation for this work, the author also reviews many of the problems he and his associates encountered and why they solved them the way they did. He also comments on the outstanding issues and likely directions for future work. Finally, this work has built on the experiences and contributions of many people. Mr. Humphrey only describes work that he was personally involved in and he names many of the key contributors. However, so many people have been involved in this work that a full list of the important participants would be impractical.     

基于复小波噪声方差显著修正的SAR图像去噪

提出了一种基于复小波域统计建模与噪声方差估计显著性修正相结合的合成孔径雷达(Synthetic Aperture Radar,SAR)图像斑点噪声滤波方法。该方法首先通过对数变换将乘性噪声模型转化为加性噪声模型,然后对变换后的图像进行双树复小波变换(Dualtree Complex Wavelet Transform,DCWT),并对复数小波系数的统计分布进行建模。在此先验分布的基础上,通过运用贝叶斯估计方法从含噪系数中恢复原始系数,达到滤除噪声的目的。实验结果表明该方法在去除噪声的同时保留了图像的细节信息,取得了很好的降噪效果。     

How do children do mathematics with LOGO?

Abstract  This paper considers some results of a study designed to investigate the kinds of mathematical activity undertaken by children (aged between 8 and 11) as they learned to program in LOGO. A model of learning modes is proposed, which attempts to describe the ways in which children used and acquired understanding of the programming/mathematical concepts involved. The remainder of the paper is concerned with discussing the validity and limitations of the model, and its implications for further research and curriculum development.