基于Flexible ICA的睡眠EEG及EOG中心电伪差的消除

提出了一种采用自适应非线性函数的ICA学习算法,Flexible ICA算法,并将其应用于睡眠EEG自动分期的前期预处理中,用于消除采集到的各通道信号中的心电伪差.实验结果证明,Flexible ICA算法能够快速有效的消除各通道的心电伪差,为后期的睡眠EEG自动分期打下了良好的基础.     

New spectral detection and elimination test algorithms of ECG and EOG artefacts in neonatal EEG recordings

New methods for the detection of ECG and EOG artefacts in the EEG are introduced, which can also be used for the evaluation of the quality of the elimination procedure. These algorithms are based on the estimation of the power or coherence spectrum by means of FFT. The advantage of this method is that the EEG spectrum is monitored by the test algorithm. The spectrum will be plotted if no influence of the ECG and EOG can be found. On the other hand, if artefacts are detected the correction of the EEG time series will be carried out and the spectrum of the corrected EEG time series will be plotted after repeated monitoring by the test algorithm.     

Dynamics of Parameters of Low-Amplitude Hand Movements in a Repetitive Motor-Cognitive Task

Neuroscience and Behavioral Physiology - In contrast to the development of muscle adaptations associated with overstrain, insufficient stretching, overloading, and underloading, use of short-term...     

Changes in the Power Levels of Cortical EEG Rhythms in Cats during Training Using Acoustic Feedback Signals

Chronic experiments on two conscious cats were performed to study the dynamics of the ratios of spectral power levels of beta and theta rhythms and neuron activity in the dopaminergic system of the ventral tegmentum during EEG feedback sessions. Training was performed using a model in which the level of sound signals presented to the animals decreased as the spectral power ratios of the EEG beta and theta rhythms recorded in the frontal leads increased. In a control series, the changes in the sound signal level were independent of the ongoing EEG. These experiments showed that the ratio of the spectral power levels of the beta and theta rhythms changed during feedback sessions, with increases in the spectral power of the beta rhythm and decreases in the spectral power of the theta rhythm. These changes were accompanied by increases in the activity of presumptive dopaminergic neurons in the ventral tegmentum.     

基于典型相关分析和小波变换的眼龟伪迹去除

目的针对脑电信号中眼电伪迹去除尚存在的问题,提出一种基于典型相关分析与小波变换的（wavelet—enhanced canonical correlation analysis,wCCA）自动去除眼电伪迹的算法。方法首先,充分利用脑电信号和眼电伪迹的空间分布特征,将基于典型相关分析的盲源分离算法分别应用于左右脑区的混合信号中,从而保证典型相关分析分解得到的第一个典型相关变量（即左右脑区之间的最公共成分）,就是眼电伪迹分量。然后为了恢复泄漏在该伪迹分量中的脑电成分,对伪迹分量进行小波阈值滤波,将高于某一阈值的小波系数置零,而保留低于阈值的系数。结果与其他三种基于盲源分离去除眼电伪迹的方法相比较,该方法在有效地自动去除眼电伪迹的同时,很好地保留了潜在的脑电信号,去除效果明显优于其他三种方法。结论由于该算法简单,处理速度较快,因此应用于实时的脑机接口系统中更具优越性,为后续脑电信号的特征提取和分类分析提供了良好的基础。     

Functional Hemispheric Asymmetry Assessment in a Visual Language Task Using MEG

We used magnetoencephalography (MEG) to assess the degree of hemispheric activation in eleven normal, right-handed subjects with no history of neurological disorder or learning disability during performance of a word- and a face-recognition tasks. Neuromagnetic activity was recorded using a whole-head system, and the sources of the recorded magnetic fields were modeled as single equivalent current dipoles. Early (<200 msec) cerebral activation, defined by the number of dipoles identified by the data-fitting algorithm, was localized in the occipital cortex during both tasks, as expected. During the language task, the extent of the later (>200 msec) cerebral activation was approximately double in the left hemisphere in almost all subjects, involving temporal and temporoparietal areas. In contrast, during the face-recognition task, the corresponding activation was mostly symmetrical across the two occipital lobes, also involving the posterior-inferior aspect of the right temporal lobe. Our results suggest that the MEG is a suitable method of assessing noninvasively hemispheric specialization for language.     

基于独立元分析和联合小波熵检测多导联ECG信号的QRS

QRS波群的准确定位是ECG信号自动分析的基础。为提高QRS检测率,提出一种基于独立元分析(ICA)和联合小波熵(CWS)检测多导联ECG信号QRS的算法。ICA算法从滤波后的多导联ECG信号中分离出对应心室活动的独立元;然后对各独立元进行连续小波变换(CWT),重构小波系数的相空间,结合相空间中的QRS信息对独立元排序;最后检测排序后独立元的CWS得到QRS信息。实验对St.Petersburg12导联心率失常数据库及64导联犬心外膜数据库测试,比较本文算法与单导联QRS检测算法和双导联QRS检测算法的性能。结果表明,该文算法的性能最好,检测准确率分别为99.98%和100%。     

Issues relating to the subtraction phase in EOG artefact correction of the EEG.

An important method for removing the effect of ocular artefact from the EEG is 'EOG correction'. This method estimates the proportion of ocular artefact that is in the EEG, and removes it by subtraction. To date, EOG correction research has focused on problems relating to the estimation of the correction coefficients. Using both mathematical rationale and empirical data, this paper addresses issues relating to the subtraction phase, such as the magnitude of error that can be expected due to EOG correction. Using ERP methodology, principal component and regression analyses, it is shown that the N1P2 complex propagates forward to the horizontal and radial (but not vertical) electrooculograms (EOG), and it is shown mathematically that this will result in EOG-correction error. Assuming an accurate estimate of ocular contamination of the EEG, maximal subtraction-phase error of the N1P2 complex was found to be a prefrontal attenuation of 15-22%, decreasing to central and occipital enhancements of 3-4% and 13-14%, respectively. The magnitude of this subtraction-phase error is compared to between-subject ERP variability and to error associated with EOG rejection (omitting data contaminated by ocular artefact). It is argued that such EOG correction error is small relative to both artefact rejection procedures and to normal variability found in ERP studies, and that it is less pernicious than artefact rejection procedures.     

Automatic Seizure Detection in Rats Using Laplacian EEG and Verification with Human Seizure Signals

Automated detection of seizures is still a challenging problem. This study presents an approach to detect seizure segments in Laplacian electroencephalography (tEEG) recorded from rats using the tripolar concentric ring electrode (TCRE) configuration. Three features, namely, median absolute deviation, approximate entropy, and maximum singular value were calculated and used as inputs into two different classifiers: support vector machines and adaptive boosting. The relative performance of the extracted features on TCRE tEEG was examined. Results are obtained with an overall accuracy between 84.81 and 96.51%. In addition to using TCRE tEEG data, the seizure detection algorithm was also applied to the recorded EEG signals from Andrzejak et al. database to show the efficiency of the proposed method for seizure detection.     

Correction of EOG Artifacts in Event-Related Potentials of the EEG: Aspects of Reliability and Validity

Correction of EOG artifacts using a regression approach is evaluated in terms of reliability and validity. Transmission rates are estimated for eight EEG channels in 67 subjects. The trimmed group means of these rates are shown to provide reliable measures. Eye artifact correction based on these group means is superior to the conventional rejection in terms of reducing correlation between EOG and EEG.     

Peak Alpha Frequency of EEG during a Mental Task: Task Difficulty and Hemispheric Differences

To investigate the effect of task difficulty on the alpha wave, bilateral EEGs were recorded from frontal and occipital locations from 5 male and 5 female students while they were engaged in two arithmetic (simple addition, SA, and complex addition, CA) and two visuo-spatial (visual imagery, VI, and mental rotation, MR) tasks. During both the arithmetic and the visuo-spatial tasks, peak alpha frequency of power spectrum increased significantly above the resting level. Moreover, the frequency shift was significantly larger in the CA and MR conditions than in the SA and VI conditions. The shift increased as the task difficulty increased. A hemispheric effect was found: the peak alpha frequency increased in the left rather than in the right during the arithmetic tasks whereas it increased in the right rather than in the left during the visuo-spatial tasks.     

Pattern Recognition of EEG Signals and Applications in Robotics

With the rapid development of brain computer interface (simply called BCI),electroencephalography (EEG) will be another interesting bio-electrical signal applied in robotics after EMG.In order to realize it finally,the accurate measurement and pattern recognition of EEG signal must be a very important and elementary research objective.Based on our current researches and some reports from the other international colleagues in the field,we deeply discuss the basic characteristics of EEG signal,the development and selection of EEG measurement system,feature extraction and recognition methods of EEG signal,and then review EEG‘s applications in robotics as well as the future research trends in this paper.     

基于脑肌电融合的混合脑机接口研究

动作模式识别是脑机接口技术的核心内容之一。针对目前脑机接口动作识别模式单一、识别率低等问题,基于混合脑机接口思想,提出一种脑电和肌电特征融合策略,可实现单侧肢体不同动作模式的有效分类,进而可用于脑机接口技术。同步采集9名健康受试者单侧手腕屈/伸两种动作模式下的脑电信号和表面肌电信号,分别提取脑电信号事件相关去同步化特征和表面肌电信号的积分肌电值特征,构建基于支持向量机和粒子群优化算法的脑肌电融合及运动模式识别模型,通过调整“特征融合系数”来实现动作模式最优分类,从而提高模式识别的准确率;进一步通过递降健康人的肌电信号幅值来模拟患者和运动疲劳状态下的肌电信号,验证所提出方法对动作模式识别的有效性。实验结果表明,基于脑肌电融合特征的动作模式识别率(98%)比单纯依靠脑电特征的识别率(73%)提高25%;在运动疲劳状态下,基于脑肌电融合特征的识别率稳定在80%以上,比单纯依靠肌电特征的识别率提高14%。可见,脑肌电融合策略能提高动作模式识别的准确性和鲁棒性,为混合脑机接口技术提供条件。     

Event Related Potentials and EEG Components in a Semantic Memory Search Task

This study examined the effects of memory search and related processes on both time and frequency domain components of electroencephalographic activity. More specifically, we were interested in the relationship between EEG and event-related potential (ERP) components as a function of memory load and response type. Subjects performed a semantic memory search task in which they matched word probes to category labels. Consistent with previous studies, reaction time increased and accuracy decreased with increasing memory loads. A negative component of the ERP (N400) was found to reflect semantic mismatch: N400s were larger for the nontargets than for the targets. Two ERP components were found to be reciprocally related to memory load. P300 decreased and Negative Slow Wave increased in amplitude with increases in the size of the memory set. These two ERP components were reflected by different components in a Principal Components Analysis. The power in the theta band (5-7 Hz) also increased as a function of memory load and appears to be functionally and topographically related to the Negative Slow Wave in the ERP. It is argued that both measures are jointly determined and reflect the difficulty of the conceptual operations during memory search.     

基于扩散模型的心电信号基线漂移去除法

ECG信号的基线漂移直接影响波形的幅值及时程测量精度,快速、有效的基线漂移去除法是ECG信号处理的重点研究内容.提出一种基于扩散模型的ECG基线漂移信号去除法,通过对有基线漂移的ECG信号进行一系列的线性扩散,使这些信号接近于漂移的基线,从而分离出ECG信号,较好地保留了ECG主要波形的形状及其时程关系.利用合成信号的仿真结果显示,扩散模型可较好地将低频成分分离出来,且合成波的频率相差越大,其分离效果越好,显示其在ECG信号基线漂移去除中良好的应用前景.     

The volume conductor may act as a temporal filter on the ECG and EEG

The influence of the volume conductor on the EEG, MEG, fetal ECG and fetal MCG is studied by means of simulations. The assumption that the Maxwell equations can be used in a quasi-static approximation is reconsidered and the fact that the conductivity of human tissue is frequency dependent is taken into account. It is found that displacement currents have a substantial effect on the fetal ECG and to a lesser degree on the fetal MCG. Moreover, the frequency dependence of the conductivity of the tissues within the head may have a considerable effect on the EEG.     

Imaging and Quantitative Assessment of Long Bone Vascularization in the Adult Rat Using Microcomputed Tomography

The objective of this study was to develop and validate a technique for both 3D imaging and quantification of the vascular network of bone tissue in the rat. Five month‐old male Wistar rats were divided into tail‐suspension (21 days) and control groups. Sixty percent barium sulfate solution was infused into the vena cava. The tibiae were evaluated in 2D and 3D before and after decalcification, using conventional microcomputerized tomography (μCT) at 10 and 5 μm resolution and synchrotron radiation (SR) μCT. The perfusion technique and tomography exhibited excellent bone vasculature imaging. Significant positive correlations were observed between 2D histomorphometric and 3D μCT vascular parameters (P < 0.05). 3DμCT discriminated significant changes of vessel structures in unloading condition: vessel number decreased by 25%, (P < 0.005), vessel separation increased by 27%, P < 0.01. SRμCT could image sinusoid clusters in bone. μCT is an accurate and reproducible technique for 3D quantitative evaluation of long bone vascularisation in the rat. Anat Rec, 2010. © 2009 Wiley‐Liss, Inc.