非线性动力学在脑电分析中的应用

非线性科学于20世纪60年代发展起来,被誉为20世纪自然科学的“第三次革命”,己广泛应用于生物、物理、经济、通讯及天文学等领域。脑电图(EEG)反映了作为非线性系统的大脑的电活动,体现出混沌行为。在癫痫病症的EEG研究中,混沌特性得到了很好的证明。在精神分裂症和老年痴呆等病症的EEG研究中,混沌的作用也体现得越来越明显。本文综述了近年来非线性动力学在脑电信号分析中应用的进展,以期获得在健康和疾病状态下对大脑神经动力系统的更好理解。     

脑电图与早产儿脑损害的相关性研究

脑电图（Electroencephalography EEG）是观察早产儿（premature infants）脑损害的敏感方法。急性和慢性EEG的改变与早产儿以后的神经和认知功能异常有相关性,应用神经生理学的方法诊断早产儿脑损害,早期持续在ICU病房的EEG监测和在以后阶段的EEG检查相结合是比较理想的手段。     

焦磷酸测序技术其在分子生物学领域的应用

焦磷酸测序技术是一项新型DNA测序技术。在DNA聚合酶、ATP硫酸化酶、荧光素酶和三磷酸腺苷双磷酸酶4种酶的协同作用下,将引物上每个dNTP聚合与一次荧光信号释放偶联起来,通过检测荧光的释放和强度,达到实时测定DNA序列的目的。操作中不需要电泳、样品标记和染色,具有高度的可重复性,并行性和自动化特点,本综述了焦磷酸测序技术的基本原理,测序过程和它在SNPs研究,病原微生物的快速鉴定、病因学分析、法医鉴定等方面应用。     

核磁共振技术在生物物理学领域中的应用

核磁共振波谱法(NMR)是利用核磁共振波谱对纯化合物进行结构测定,并定性或定量分析其微结构的一种研究手段.随着脉冲傅立叶变换技术和超导磁体的发展和普及.15N和31P等核磁共振谱(以15N和31P原子为测定对象得出的图谱),以及诸如二维核磁共振谱等新技术和新方法不断涌现并完善,核磁共振波谱法在生物学领域的应用也越来越广泛.在调研大量国外文献基础上,介绍NMR方法在生命科学研究方面的应用研究成果.     

脑电双频指数监测技术及其临床应用

适宜的麻醉深度是保证患者的生命安全和创造良好手术条件的关键。脑电双频指数(bispectralindex,BIS)是用于监测镇静程度的一种新方法,自从临床应用以来它已得到多方面关注和研究,本文就其概念、原理及临床应用等方面进行综述。     

功率谱熵在痫性发作大鼠脑电检测中的应用研究

目的:研究功率谱熵在痫性发作大鼠脑电检测中的应用。方法:采用青霉素在大鼠海马微注射制备急性痫性发作模型,以深部电极记录大鼠原始脑电信号,将24只SD大鼠随机分成四组,即正常组(A),对照组(B),单电极组(C),多电极组(D)。C、D组大鼠经致痫后观察未发作期、发作前期、发作期和发作后期四期脑电信号的变化,运用谱熵对四期脑电信号进行分析,并与A、B组进行对比。结果:C组和D组脑电功率谱熵显示两组发作期与未发作期、发作前期、发作后期比较有显著差异(P0.05),发作期明显低于其它各期;未发作期和发作前期相比有明显差异(P0.05),发作前期较未发作期降低;将D组大鼠海马致痫灶(a)及其同侧附近(b)、对侧(c)三点发作各期脑电功率谱熵进行对比分析,发作前期和发作期a、b、c三点比较有明显差异(P0.05),a点最低,c点的功率谱熵值最高。结论:功率谱熵可以预报痫性发作并可对癫痫病灶的定位提供一定的帮助。     

脑电双频指数监测技术及其临床应用

适宜的麻醉深度是保证患者的生命安全和创造良好手术条件的关键。脑电双频指数（bispectralindex,BIS）是用于监测镇静程度的一种新方法,自从临床应用以来它已得到多方面关注和研究,本文就其概念、原理及临床应用等方面进行综述。     

40例慢性脑型血吸虫病的脑电图分析

目的:了解脑型血吸虫病脑电图(EEG)的脑电活动状况,为临床诊断与治疗提供参考。方法:收集1997~2004年临床诊断为脑型血吸虫病的40例EEG资料,主要分析异常EEG的脑电活动状况与异常程度、临床分型及预后的关系。结果:31例出现不同程度的EEG异常改变,异常率为77.5%,其中癫痫性为70%;脑瘤型为100%。绝大部分EEG检查是患者经治疗后作的。治疗前后均作了EEG检查的仅9例。治疗前,9例均有不同程度异常,治疗后7例有不同程度改善,2例恢复正常。结论:EEG对脑型血吸虫病的诊断及预后的评价有参考价值。     

抽动障碍临床特点与脑电图关系的研究进展

抽动障碍(Tic disorder,TD)是一种儿童期发病且主要侵犯神经系统的疾病。临床工作中发现部分患儿脑电图(electroencephalogram,EEG)明显异常,提示患儿脑功能障碍与疾病严重程度有关;TD患儿治疗后EEG变化特点也对临床医生选择何种治疗方式有指导意义。     

视频脑电图与常规脑电图在癫痫患儿诊断和定位中的应用价值对比研究

目的:比较视频脑电图(VEEG)与常规脑电图(REEG)在癫痫患儿诊断和定位中的应用价值,为癫痫诊断提供依据。方法:对2014年1月~2016年12月间本院收治的有临床症状拟诊断为癫痫的102例患儿的临床资料进行回顾性分析,比较VEEG与REEG两种方法痫样放电检出率、临床发作检出率、睡眠期检出率以及痫灶定位中的诊断价值。结果:102例患儿中,VEEG检测到痫样放电80例,痫样放电检出率为78.43%,REEG检测到痫样放电42例,痫样放电检出率为41.18%,VEEG痫样放电检出率显著高于REEG(P0.05)。VEEG临床发作检出率为48.75%,显著高于REEG临床发作检出率的14.29%(P0.05)。VEEG检测出睡眠期痫样放电检出率为46.25%,高于觉醒期痫样放电检出率的12.50%(P0.05)。VEEG睡眠期各电图时相痫样放电检出率比较,组间差异均有统计学意义(均P0.05)。根据VEEG确定39例癫痫患儿痫样放电起源部位为额区9例、颞区10例、额颞区9例、枕区4例、中央区4例、颞枕后区3例。结论:VEEG对癫痫患儿的脑部痫样放电检出率和临床发作检出率均明显优于REEG,同时定位诊断效果更优,值得临床推广应用。     

Providing QoS in Bluetooth

Bluetooth polling, also referred to as Bluetooth MAC scheduling or intra-piconet scheduling, is the mechanism that schedules the traffic between the participants in a Bluetooth network. Hence, this mechanism is highly determining with respect to the delay packets experience in a Bluetooth network. In this paper, we present a polling mechanism that provides delay guarantees in an efficient manner, and we evaluate this polling mechanism by means of simulation. It is shown that this polling mechanism is able to provide delay guarantees while saving as much as possible resources, which can be used for transmission of best effort traffic or for retransmissions.Rachid Ait Yaiz (1974) received his BS in Electrical Engineering from the Technische Hogeschool Arnhem, the Netherlands, in 1996 and his MSc in Electrical Engineering from the University of Twente, the Netherlands, in 1999. He received his Ph.D. in Telecommunications from the same university in 2004. Currently, he works for TNO Telecom. His research interests include mobile and wireless networks, and he is particularly interested in the area of quality of service over mobile and wireless networks.Geert Heijenk (1965) received his MSc in Computer Science from University of Twente, the Netherlands, in 1988. He worked as a research staff member at the same university and received his Ph.D. in Telecommunications in 1995. He has also held a part-time position as researcher at KPN research, the Netherlands, from 1989 until 1991. From 1995 until 2003, he was with Ericsson EuroLab Netherlands, first as a senior strategic engineer, and since 1999 as a research department manager. From 1998 until 2003 he was also a part-time senior researcher at the University of Twente. Currently, he is a full-time associate professor at the same university. His research interests include mobile and wireless networks, resource management, and quality of service.     

Walk-In Bridge Scheduling in Bluetooth Scatternets

Bluetooth scatternets may be operated in a loosely coupled mode, called Walk-In Bridge Scheduling, in which the master polls all of its slaves and bridges using E-limited service. Using the theory of queues with vacations, we derive the stability criteria for packet queues in piconet masters, slaves, and bridges. We show that the stability of the slave queues is more critical under high traffic locality, whereas the stability of the bridge queues becomes progressively more important as the non-local traffic increases. Our analysis shows that the limited exchange mode, in which the bridge residence time in a piconet is limited, performs better and has a wider stability region than the complete exchange mode in which the bridge stays in the piconet until all queued packets are exchanged. Simulations show that this scheduling approach offers good performance and excellent scalability, while maintaining scatternet stability.Vojislav B. Mii received his PhD in Computer Science from the University of Belgrade, Yugoslavia, in 1993. He is currently Assistant Professor of Computer Science, at the University of Manitoba in Winnipeg, Manitoba, Canada. Previously, he has held posts at the University of Belgrade, Yugoslavia, and the Hong Kong University of Science and Technology. His research interests include systems and software engineering and modeling and performance evaluation of wireless networks. He is a member of ACM, AIS, and IEEE.Jelena Mii received her PhD degree in Computer Engineering from the University of Belgrade, Yugoslavia, in 1993. She is currently Associate Professor of Computer Science at the University of Manitoba in Winnipeg, Manitoba, Canada. Previously, she has been with the Hong Kong University of Science and Technology. Her current research interests include wireless networks and mobile computing. She is a member of IEEE Computer Society.Ka Lok Chan received his MPhil degree in performance of Bluetooth networks at the Hong Kong University of Science and Technology.     

复杂度脑电地形图研究

脑电地形图是近年脑电分析的热点之一。通过对各种复杂度算法的分析得出,近似熵由于所需要的时间序列长度较短,大大减少了脑电非平稳性所带来的困难,且无需粗粒化,在对生物医学信号的复杂度分析中有其一定的优点,采用近似熵对多道脑电信号的复杂度运算结果,通过空间插值,构建复杂性动态脑地形图,以便于观察大脑各部ＥＥＧ信号复杂度在同一时刻的相对强弱关系和这种关系随时间的变化。并通过对一些脑疾病患者脑电数据的分析,     

脑电信息处理

脑电信息处理是脑功能研究重要组成部分。本文介绍了脑电信息处理的前沿领域,包括诱发电位、事件相关电位（ＥＲＰ）、正弦调制光（声）诱发脑电、４０ＨｚＥＲＰ和脑电非线笥动力学研究,并论及了认知活动与分形维数的关系。     

基于蓝牙4.0的便携式睡眠监测仪的研制

目的:实时监测睡眠状况,从而帮助人们特别是老人找到影响睡眠的原因。方法:设计了一个低功耗便携式睡眠监测仪,它是通过加速度传感器采集腕动信号、蓝牙4.0低功耗无线传输、Micro-SD卡存储、上位机显示等实现对睡眠状态的检测。为了验证睡眠监测仪的准确性,本文采用了视频分析方法,并且对不同人群进行监测。结果:研制的睡眠监测仪具有便携低功耗等特点,能够准确监测睡眠状态。结论:睡眠监测仪的研制对使用者特别是老人帮助很大,能够帮助使用者方便适时了解自己的睡眠状况,找到影响睡眠原因和改善睡眠质量方法。     

快速独立分量分析及其在脑电信号处理中的应用

独立分量分析(IndependentComponentAnalysis,ICA)是一种基于信号统计特性的盲源分离方法,由于其分离的信号之间是互相独立的,所以在生物电信号去除干扰和伪迹、信号分离以及特征提取等方面有很大的潜在价值。本文提出了一种改进的快速ICA方法,提高了收敛速度。通过仿真,证明这种方法的优越性。最后利用该方法去除脑电中眼动伪迹,达到了较好的效果。     

EEG的信息熵分析

用非线性动力学观点来分析ＥＥＧ认为它可能是一个不稳定混沌态,并提出了用信息熵的方法来分析这一混沌态的结构特征。临床观察发现在不同功能下其特征是不一样的,并发现精神病人中信息传递特征参数有“倒置“现象,这对ＥＥＧ分析和临床脑电诊断都是有很大意义的。     

Awake EEG Disregulation in Good Compared to Poor Sleepers

This study was designed to test a disregulation model of sleep deprivation by assessing the ability of good sleepers compared to poor sleepers to shift daytime EEG patterning to changing environmental demands. Ten good and ten poor sleepers were identified from a sample of 110 college students who completed the Pittsburgh Sleep Quality Inventory (PSQI). EEG and SCR were recorded during a five task assessment session, including: (1) pre-baseline, (2) eyes open at rest, (3) eyes closed at rest, (4) sensory attentiveness (listening to an audio book clip), and (5) cognitive effort (a higher level cognitive flexibility task). A significant Group × Task interaction, F (3, 16) = 4.81, p = . 01 was attained on the theta data. Specifically, for good sleepers, theta decreased from the “eyes open at rest” to the “sensory attentiveness” tasks, while poor sleepers showed the opposite pattern. This pattern of theta suppression was found in 70% of the good sleepers and only 20% of the poor sleepers. No between group differences were noted in the SCR data, supporting a brain disregulation model, rather than a general psychophysiological stress model. Partial funding for this research was provided by the office of Research, Grants, and Contracts at the University of Tennessee at Martin.     

动态脑电图与常规脑电图应用于病毒性脑炎诊断的效果分析

目的:探讨动态脑电图与常规脑电图应用于病毒性脑炎的应用价值。方法:选取150例病毒性脑炎患者,随机分为两组,每组各75例,常规脑电图(REEG)组采用常规脑电图检查,动态脑电图(AEEG)组采用动态脑电图检查;观察并记录脑电图异常率,不同程度病情脑电图异常率的例数,评价动态脑电图与常规脑电图对病毒性脑炎的检测灵敏度和准确度。结果:AEEG组检出的脑电图异常率明显高于REEG组(P0.05)。不同程度病情脑电图检出的患者比例,两组相比,差异没有统计学意义(F=-0.085,P0.05)。REEG组中,轻度与中度病毒性脑炎检出率相比,差异没有统计学意义(P0.05),中度与重度病毒性脑炎检出率相比,差异没有统计学意义(P0.05),重度病毒性脑炎检出率明显高于轻度(P0.05)。AEEG组中,轻度与中度病毒性脑炎检出率相比,差异没有统计学意义(P0.05),重度病毒性脑炎检出率明显高于中度和轻度(P0.05),AEEG组重度病毒性脑炎检出率明显高于REEG组(P0.05)。结论:动态脑电图作为一种无创性检查,对于病毒性脑炎具有极好的检出率,灵敏度高,适用于病毒性脑膜炎的早期辅助诊断。     

Responses to tonic heat pain in the ongoing EEG under conditions of controlled attention

To confirm the existence of an ongoing electroencephalogram (EEG) pattern that is truly suggestive of pain, tonic heat pain was induced by small heat pulses at 1?°C above the pain threshold and compared to slightly less intense tonic non-painful heat pulses at 1?°C below the pain threshold. Twenty healthy subjects rated the sensation intensity during thermal stimulation. Possible confounding effects of attention were thoroughly controlled for by testing in four conditions: (1) focus of attention directed ipsilateral or (2) contralateral to the side of the stimulation, (3) control without a side preference, and (4) no control of attention at all. EEG was recorded via eight leads according to the 10/20 convention. Absolute power was computed for the frequency bands delta (0.5–4?Hz), theta (4–8?Hz), alpha1 (8–11?Hz), alpha2 (11–14?Hz), beta1 (14–25?Hz), and beta2 (25–35?Hz). Ratings were clearly distinct between the heat and pain conditions and suggestive for heat and pain sensations. Manipulation of attention proved to be successful by producing effects on the ratings and on the EEG activity (with lower ratings and lower EEG activity (theta, beta1, 2) over central areas for side-focused attention). During pain stimulation, lower central alpha1 and alpha2 activity and higher right-parietal and right-occipital delta power were observed compared to heat stimulation. This EEG pattern was not influenced by the manipulation of attention. Since the two types of stimuli (pain, heat) were subjectively felt differently although stimulation intensities were nearby, we conclude that this EEG pattern is clearly suggestive of pain.