脑机接口中基于ICA-RLS的EOG伪迹自动去除

眼电(EOG)伪迹是基于脑电(EEG)的脑机接口系统中最重要的干扰。为自动去除这种干扰,提出了基于ICA-RLS的EOG伪迹自动去除算法。首先,ICA将多个导联EEG信号分解成数目相等的若干个独立分量(ICs)。然后,计算并依据每个IC的峰态系数,自动地从ICs中识别出EOG分量。最后,识别出的EOG分量用作RLS自适应滤波器的参考信号,并用该滤波器对原始EEG进行滤波,在无需记录EOG情况下实现EOG伪迹的自动去除。用提出算法对2008年脑机接口竞赛数据进行处理,从去除伪迹后信号的观察、信息保留完整性和最终分类结果的计算进行评价。与标准的ICA算法相比,提出算法能够更好去除EOG伪迹,同时获取更高的分类正确率。     

基于独立分量分析的脑电信号消噪

脑电信号中往往含有各种形式的噪声干扰信号。这些干扰成分包括眼电、心电伪迹以及工频干扰等。由于干扰信号和脑电信号在频域上相互重叠,因此用时域或频域滤波的方法难以有效地消除脑电信号中的干扰成分。独立分量分析(Independent Component Analysis,ICA)是20世纪90年代发展起来的一种新的盲源分离方法(Blind Source Separation,BSS),将ICA方法应用于实测脑电信号的处理,获得非常理想的消噪效果。     

无先验参考的脑电信号伪迹去除方法

在深入分析脑电信号各伪迹成分特征的基础上,结合传统滤波方法,提出了一种不需要眼电信号参考的脑电信号伪迹去除方法。脑电信号原始数据可视作由纯净脑电信号、环境噪声、动作杂波及人体自身伪迹成分所构成的混合信号,利用传统滤波方法去除环境噪声及动作杂波,结合盲源分离算法提取人体自身伪迹成分并完成伪迹成分自动识别与去除以及纯净脑电信号的重构工作,以实现纯净脑电信号有效提取过程。经实验验证,该无先验参考的脑电信号伪迹去除方法切实可行,可有效去除伪迹,提高脑电信号信噪比。     

一种基于滑动均值滤波的疲劳脑电信号识别方法

利用神念科技脑电产品Mind Wave设备来采集脑电信号,通过设计窗口均值滤波及自适应补偿算法,并结合T检验来对脑电信号进行处理,以识别出脑电信号的疲劳度程度。在Min GW和Eclipse开发环境下,利用Java语言实现脑电信号识别系统,实验结果验证了该方法的有效性。     

基于表情辅助的假手脑控方法

针对传统纯意念运动想象脑控范式和稳态视觉诱发脑控范式存在范式训练难度高、设备集成复杂及高成本、不易随身携带等问题,借助表情辅助脑电信号适应性广、识别率高和易于便携化系统集成的优势,提出了基于表情辅助的假手脑控方法;研究构建了一种基于表情辅助的假手便携可穿戴脑控系统,包括硬件选型设计与系统组建,及表情辅助脑电信号分类识别算法和假手控制算法的设计研究与软件模块开发等,实现提眉、皱眉、左撇嘴和右撇嘴4种辅助表情脑电信号的检测识别,对应完成假手的手指张开、手指闭合、手腕内旋和手腕外旋4个动作的控制,并进行在线实验验证。结果表明：基于表情辅助的假手脑控方法不仅优于传统的稳态视觉诱发脑控范式（去掉了系统中原所必须的稳态视觉诱发器）,而且优于纯意念运动想象脑控范式,平均在线识别与控制准确率高于85%。     

眼电伪迹自动去除方法的研究与分析

脑电信号采集时很容易受到眼电信号的干扰,从而影响脑机接口系统的性能。为此,提出一种基于离散小波变换(DWT)和典型相关分析(CCA)的眼电伪迹自动去除方法,即 DCCA 法。首先,对采集的多导脑电信号和眼电信号进行离散小波变换,获得多尺度小波系数,并利用典型相关分析去除小波系数间的相关性,得到互不相关的典型小波系数;进而,利用相关系数判别眼迹成分,将相应典型小波系数置零并依次采用 CCA逆变换和 DWT逆变换重构剔除眼电伪迹后的脑电信号。基于9位实验者的4种眼电数据进行实验研究,并从统计学的角度对实验结果进行显著性检验。结果表明, DCCA法相对其他方法在均方根误差、信噪比方面具有显著优势,且具有较好的实时性,并表现出较强的适应能力。     

数学形态滤波在去除脑电伪迹中的应用

针对脑电信号在采集过程中容易受到伪迹(噪声)干扰的问题,提出了利用数学形态滤波器去除脑电伪迹的方法。根据脑电信号和伪迹的不同性质,采用不同的结构元素组成两级数学形态滤波器,对受到工频干扰的脑电信号进行处理,并通过信噪比和均方误差对滤波效果进行评价。仿真结果表明,与一级数学形态滤波器和小波软阈值法相比,该方法不仅可以有效地抑制工频干扰,提高信噪比,还能够降低均方误差,较好地保持脑电信号的特征形态。     

基于SSVEP_SSA融合的混合脑机接口研究

针对目前基于体感选择性注意范式的脑机接口控制指令数少,信息传输率低等缺点,提出了一种全新的多模态混合脑机接口系统。该系统融合稳态视觉刺激(SSVEP)和体感选择性注意范式(SSA),在外部视觉和体感刺激的作用下,诱发大脑产生稳态视觉电位和事件相关去同步现象。同时,为了解决传统脑电信息特征提取中需要大量先验知识等问题,引入深度学习算法对混合脑机接口信息进行意图解码,该方法将多通道的时域信息转换成具有时-频-空域三维特征的二维特征图。对8名受试者的离线实验显示,平均识别准确率达到81. 35%,确认了所提出的基于SSVEP_SSA融合的多模态混合脑机接口是可行的,实现了脑机接口(BCI)系统的指令集扩展和高精度解码。     

结合ACF和TFBSS的心冲击伪迹抑制方法

同步脑电-功能磁共振成像(EEG-f MRI)可同时对大脑活动进行高时间和高空间分辨率观测,但磁共振扫描导致采集得到的脑电信号中包含心冲击伪迹,严重制约了同步EEG-f MRI应用的发展。为此,提出一种结合自适应梳状滤波器(ACF)与时频盲源分离(TFBSS)的心冲击伪迹抑制方法,首先估计脑电信号中心冲击伪迹的J峰位置,并根据该位置自适应调整梳状滤波器参数,对脑电(EEG)信号进行自适应梳状滤波,初步抑制其中的心冲击伪迹。然后利用TFBSS对心冲击伪迹作进一步抑制,最终获得较为清晰的EEG信号。采用临床EEG信号进行心冲击伪迹抑制实验,选择视觉效果、归一化功率谱比值和峰峰值比值评价性能。实验结果表明,所提出的方法能成功抑制心冲击伪迹;且相对于传统的心冲击伪迹抑制方法更有优势。     

基于不同频率声音刺激的脑电信号分析方法研究

本文主要研究在不同频率声音刺激下的脑电信号特征.通过设计实验方案获取脑电数据,利用小波变换将脑电数据分解为不同频带信号,实现各频带信号的功率谱计算,应用模极大值检测脑电信号中的突变点,提取大脑在不同频率声音刺激下的特征,分析了人脑与声音刺激的关系,实验结果对脑机接口以及盲人导行等研究具有重要价值.     

飞行时间质谱仪射频四极杆驱动器的研制

针对自制垂直引入式飞行时间质谱仪（orthogonal extraction time-of-flight mass spectrometer, O-TOFMS）的需要,运用直接数字频率合成 (direct digital frequency synthesis,DDS)技术,研制了射频四极杆的高压射频驱动电路装置。该驱动器频率可调范围为0.5~2 MHz,幅度最高达到1 000 Vp-p。该射频四极杆驱动器（radio frequency quadrupole driver,RFQ Driver）可用于分子离子反应器（molecule ion reactor,MIR）和RFQ驱动,其结构简洁、成本低、性能稳定可靠。     

从光电容积图中提取脉搏率、呼吸率和心率的新方法

光电容积描记图(PPG)是一种利用光学技术无创检测人体心血管脉搏波的方法。PPG信号来源于MIMIC数据库,它含有许多生理信息。本文提出了将集合经验模态分解(EEMD)、倒谱、快速傅里叶变化和过零点检测相结合的方法,从PPG中可靠地估算脉搏率(PR)、心率(HR)和呼吸频率(RR)。首先,将PPG信号通过EEMD分解为有限个固有模态函数(IMF)。因为EEMD有自适应滤波特性,所以估算不同的生理参数时,可以用不同的IMF分量来重构信号。其次,估算脉搏率时,舍去低频含有伪迹的IMF,再通过过零点检测可以得到瞬时脉搏率。然后,估算心率时,用1 Hz~1.67 Hz(60次/分钟~100次/分钟)的IMF来重构信号,再求倒谱,选取反映心脏活动的频带来得到心率。最后,估算呼吸率时,用0.05 Hz~0.75 Hz(3次/分钟~45次/分钟)的IMF来重构信号,然后对呼吸信号求快速傅里叶变化得到频谱图,寻找频谱图中的峰值得到呼吸率。对来自MIMIC数据库的53个成人PPG信号进行了仿真。仿真结果表明使用该综合信号处理方法提取的生理参数与实际生理参数一致,且该方法有运算量小,精确度高的优点(误差不超过1.17%)。     

UPLC-MS/MS测定二苯甲烷二异氰酸酯

建立了二苯甲烷二异氰酸酯（MDI）的超高效液相色谱-串联质谱（UPLC-MS/MS）联用的分析方法。实验用甲醇作衍生试剂,将二苯甲烷二异氰酸酯衍生成二苯甲烷二氨基甲酸甲酯（MDC）,通过测定二苯甲烷二氨基甲酸甲酯来确定二苯甲烷二异氰酸酯的含量。实验采用Waters Acquity BEH C18超高效液相色谱柱,甲醇-0.1%甲酸作为梯度洗脱液,二苯甲烷二氨基甲酸甲酯在1.5 min内与其他化合物进行完全分离,经四极杆质谱选择离子监测模式检测。线性范围为2~100 μg/L,检出限为1 μg/L,相关系数0.999 4。考察了水、甲酸、甲酸铵流动相体系,以及进样量大小对样品的分离效果,发现甲酸流动相体系的分离效果优于其他两种流动相体系,同时发现在进样量大时出现平头峰。并且在优化条件下,对实际样品中游离的二苯甲烷二异氰酸酯进行了测定。     

Effect of the molecular weight on deformation states of the polystyrene film by AFM single scanning

Nanobundles patterns can be formed on the surface of most thermoplastic polymers when the atomic force microscope (AFM)‐based nanomechanical machining method is employed to scratch their surfaces. Such patterns are reviewed as three‐dimensional sine‐wave structures. In the present study, the single‐line scratch test is used firstly to study different removal states of the polystyrene (PS) polymer with different molecular weights (MWs). Effects of the scratching direction and the scratching velocity on deformation of the PS film and the state of the removed materials are also investigated. Single‐wear box test is then employed to study the possibility of forming bundle structures on PS films with different MWs. The experimental results show that the state between the tip and the sample plays a key role in the nano machining process. If the contact radius between the AFM tip and the polymer surface is larger than the chain end‐to‐end distance, it is designated as the “cutting” state that means the area of both side ridges is less than the area of the groove and materials are removed. If the contact radius is less than the chain end‐to‐end distance, it is designated as the “plowing” state that means the area of both side ridges is larger than the area of the groove and no materials are removed at all. For the perfect bundles formation on the PS film, the plowing state is ideal condition for the larger MW polymers because of the chains’ entanglement. SCANNING 35:308‐315, 2013. © 2012 Wiley Periodicals, Inc.     

Rapid one-of-a-kind production

To shorten the product development cycle time and reduce the cost at the same time, which is very critical for the survival of those small and mid-sized one-of-a-kind production (SMOKP) companies, various computer communication, simulation and computer aided engineering and management techniques have been widely used in these SMOKP companies. However, according to our study, the applications of these advanced computer technologies in these SMOKP companies are lack of system integration and synergy, which result in communication errors, reworks, duplications and hence a longer product development lead time and a higher cost. To solve this problem, an inter/intranet based computer aided rapid product development system is presented in this paper. This system consists of a number of inter/intranet based computer models or sub-systems for supporting rapid development of a one-of-a-kind product. It also employs a novel concurrent product development strategy called “prototype based incremental product development strategy” and an integrated product data structure called “product production structure”. Some industrial implementations of the proposed system, product development strategy and product data structure are also reported in the paper.     

汽车ESC系统DIL/HIL仿真平台设计

全面准确地标定与测试是开发车辆电子稳定控制(electronic stability control,ESC)系统的关键环节。车辆控制过程是典型的强非线性系统,建立精确的车辆模型比较困难,驾驶员模型也很难准确模拟紧急工况下驾驶员的真实反应。在仿真系统中将难以精确建模的液压制动系统、ESC压力调节单元、转向及电子节气门装置采用真实硬件,并在试验平台中嵌入真实驾驶员,基于Matlab/Simulink/dSPACE环境和车辆动力学软件veDYNA,开发硬件在环(hardware-in-the-loop,HIL)和驾驶员在环(driver-in-the-loop,DIL)的仿真试验平台,并在此平台上对所设计的ESC系统进行仿真试验研究。试验结果表明,所设计的DIL/HIL仿真平台可以大幅提高ESC系统的开发效率和测试准确性。     

Rapid one-of-a-kind production

To shorten the product development cycle time and reduce the cost at the same time, which is very critical for the survival of those small and mid-sized one-of-a-kind production (SMOKP) companies, various computer communication, simulation and computer aided engineering and management techniques have been widely used in these SMOKP companies. However, according to our study, the applications of these advanced computer technologies in these SMOKP companies are lack of system integration and synergy, which result in communication errors, reworks, duplications and hence a longer product development lead time and a higher cost. To solve this problem, an inter/intranet based computer aided rapid product development system is presented in this paper. This system consists of a number of inter/intranet based computer models or subsystems for supporting rapid development of a one-of-a-kind product. It also employs a novel concurrent product development strategy called “prototype based incremental product development strategy” and an integrated product data structure called “product production structure”. Some industrial implementations of the proposed system, product development strategy and product data structure are also reported in the paper.     

复合ICA-SVM机械状态模式分类

提出了一种新颖的、基于独立分量分析(ICA)的复合神经网络，用于不同机械状态模式的特征提取。利用支持向量机(SVM)进行最终分类。与通常的基于经验风险最小化(ERM)原理的神经网络方法相比，基于结构风险最小化(SRM)原理的支持向量机分类方法具有更好的推广能力。而借助多个独立分量分析网络，隐藏于多通道振动观测信号中的不变特征得到有效提取，从而实现了支持向量机分类器在分类能力和推广性两者间的合理平衡。     

The efficacy of back propagation neural network with delta bar delta learning in predicting the wear of carbide inserts in face milling

Face milling is a process predominantly affected by dynamic variation of cutting forces, thermo-mechanical shocks and vibration leading to catastrophic tool failure along with gradual wear of the inserts. Keeping in view the industrial importance of this process, it is necessary to devise suitable methods to predict in advance the onset of tool failure without grossly impairing the machining set-up and the job. Hence, the applicability of back propagation neural network with delta bar delta learning rule for faster convergence has been studied with the above objective. The multi sensor based tool condition monitoring strategy shows that the learning rate adaptation scheme combined with the selection of suitable process parameters drastically reduces the training time of the artificial neural network without dispensing with the prediction accuracy.     

血清AFP、CA199、GGT、ALP联检肝癌早期诊断价值

目的:探讨甲胎蛋白(AFP)、糖类抗原199(CA199)、谷氨酰转肽酶(GGT)和碱性磷酸酶(ALP)单独或联合检测对原发性肝癌(PHC)的早期诊断价值。方法:本研究为回顾性研究,筛选2016年-2019年本院87例原发性肝癌(PHC)患者、105例慢性乙肝患者及104例健康志愿者,收集不同组首次入院和体检外周血检测数据和其他临床资料。比较各血清指标在组间差异性,分析了血清学指标与入组PHC临床分期和病理分型的相关性,进一步利用ROC曲线法分析血清指标单项与联合诊断的灵敏度、特异度。结果:AFP、CA199、GGT、ALP检测均值在PHC组均明显高于慢乙肝组和健康体检组。AFP阳性检测值与PHC临床分期(r=0.9536)和病理分型(r=0.525)呈正相关性。AFP诊断PHC灵敏度和特异性分别为60.87%和77.97%、精准度AUC为0.726。联合四项指标检测灵敏度、特异度和AUC分别为75.36%、65.64%、0.806。结论:AFP、CA199、GGT、ALP四项指标联合检测可提高原发性肝癌早期诊断的准确率,操作性强且易于推广。