NONINVASIVE DETECTION OF BRAIN ACTIVITY VARIATION UNDER DIFFERENT DEPTH OF ANESTHESIA BY EEG COMPLEXITY

Objective To detect the change of brain activity under different depth of anesthesia (DOA) noninvasively. Methods The Lempel-Ziv complexity C(n) was used to analyze EEG and its four components (delta, theta, alpha, beta), which was recorded from SD rats under different DOA. The relationship between C(n) and DOA was studied. Results The C(n) of EEG will decrease while the depth of anesthesia increasing and vice versa. It can be used to detect the change of DOA sensitively. Compared with power spectrum, the change of C(n) is opposite to that of power spectrum. Only the C(n) of delta rhythm has obvious variations induced by the change of DOA, and the variations of delta is as similar as the EEG's. Conclusion The study shows that the desynchronized EEG is replaced by the synchronized EEG when rat goes into anesthesia state from awake, that is just the reason why complexity and power spectrum appear corresponding changes under different DOA. C(n) of delta rhythm dynamic change leads to the change of EEG, and the delta rhythm is the dominant rhythm during anesthesia for rats.

The Observation on Risk of Ventilator Failure Weaning by Ultrasound bedside Monitoring of Inferior Vena Cava and Lung B Line

Objective: This study was designed to investigate risk of ventilator weaning by ultrasound bedside monitoring of the width of inferior vena cava (IVC) and the number of lung B-lines (B-lines). Methods: This study was conducted on 106 patients from January 2019 to January 2020 who had mechanical ventilation for more than 48 hours in an emergency care unit. They were clinically stable and had the criteria for weaning from the ventilator. Before Spontaneous Breathing Test (SBT) and 30 min or 120 min after SBT, the width of IVC and the number of B-lines in patients were monitored via bedside ultrasound. There were 87 cases of successful weaning as a control group and 19 cases of ventilator failure weaning as a study group. Changes of the width of IVC and the number of B-lines were compared in the different stages of SBT. Results: A total of 106 patients were included in this study. There were 87 cases of ventilator successful weaning and 19 cases failure weaning. The weaning success rate was 82.08%. The width of IVC and the number of B-lines in the study group were higher than those in the control group in same stage of SBT, the difference was statistically significant (P < 0.05), and which increased significantly with time. There was no significant difference in the width of IVC and the number of B-lines on the different stage of SBT in the control group (P > 0.05), and significant difference in the study group. Conclusion: The width of IVC and the number of B-lines monitored by bedside ultrasound can assess the risk of ventilator weaning, it may be caused by cardiopulmonary interaction.

COMPUTER-AIDED DETECTION OF THE EPILEPTIC WAVES IN EEG:A REALIZED STRATEGY BY ADOPTING MULTI-METHOD

In this thesis, a strategy realizing the computer-aided detection (CAD) of the epileptic waves in EEG isintroduced. The expert criterion, continuous wavelet transformation, neural networks, and characteristic parametermeasuremente these modern signa1 processing weapons were synthesized togetLher to form a so-called multi-method.It was estimated that the advantages of all the powerful techniques could be exploited systematically. Therefore, theCAD’s capacities in the long-term monitoring, trCaAnent and control of epilepsy might be enhanced. In this strategy,the raw EEG signals were uniformed and the expelt criterion were applied to discard most of aItifacts in them at first,and then the signals were pre-processed by continuous wavelet transformation. Some characteristic parameters wereextracted from the raw signals and the pre-processed ones. Consequently groups of eighteen parameters were sent totrain or test BP networks. By applying this theme a correct-detection rate of 84.3% for spike and sharp waves, and88.9% for sPike and sharp slow waves were obtained. In the next step, some non-linear tools wtll also be equippedwith the CAD system.

基于平均能量差的运动想象EEG通道选择和特征提取

共空间模式(CSP)广泛应用于脑电信号(EEG)的特征提取,合适的通道选择可以有效地提高CSP的分类性能,增加信噪比。根据运动想象信号的平均能量差来进行通道选择和特征提取。首先取两类运动想象信号的通道均值能量作为投票的阈值,根据投票差值统计各通道上有明显能量差值试次的数量,基于此来选择出合适的通道,然后对这些通道取能量特征进行归一化,再结合CSP空域特征利用SVM进行分类。在BCI CompetitionⅢData SetsⅣa和BCI Competition IV Dataset SetsⅠ两个数据集上进行的分类实验中,所提出的方法相比于全通道CSP,平均精度分别提高了5.7%和10.9%,通道数分别减少了74.3%和51.7%,验证了所提出的通道选择和特征提取方法的有效性。

EEG信号结合特征融合技术诊断精神分裂症和抑郁症

目的探索通过机器学习算法结合脑电信号实现对精神分裂症和抑郁症的诊断。方法分别采集33例精神分裂症患者和28例抑郁症患者的脑电信号,并将采集到的脑电图信号格式由EDF格式转化为ASCII格式,提取脑电信号的Lempel-Ziv复杂度、最大李雅普诺夫指数、Higuchi分形维数等特征。应用特征融合策略对特征进行融合,形成新的特征向量,然后利用机器学习分类算法进行分类研究。结果最终基于高斯核函数的支持向量机(SVM)的分类准确率为84.85%,其中灵敏度为89.47%,特异性为78.57%。结论通过提取EEG脑电信号特征结合机器学习算法对精神分裂症和抑郁症进行识别,对开发新型的精神分裂症和抑郁症的诊断技术具有一定的研究意义。

注意力残差网络结合LSTM的EEG情绪识别研究

基于脑电信号的情感识别已成为情感计算和人机交互领域的一个重要挑战。由于脑电信号中具有时间、空间、频率维度信息,采用结合注意力残差网络与长短时记忆网络的混合网络模型(ECA-ResNet-LSTM)对脑电信号进行特征提取与识别。首先,提取时域分段后脑电信号不同频带微分熵特征,将从不同通道中提取出的微分熵特征转化为四维特征矩阵;然后通过注意力残差网络(ECA-ResNet)提取脑电信号中空间与频率信息,并引入注意力机制重新分配更相关频带信息的权重,长短时记忆网络(LSTM)从ECA-ResNet的输出中提取时间相关信息。实验结果表明:在DEAP数据集唤醒维和效价维二分类准确率分别达到了97.15%和96.13%,唤醒-效价维四分类准确率达到了95.96%,SEED数据集积极-中性-消极三分类准确率达到96.64%,相比现有主流情感识别模型取得了显著提升。

基于深层图卷积的EEG情绪识别方法研究

针对浅层图卷积提取的局部脑区空间关联信息对情感脑电表征不足的问题,本文提出了一种深层图卷积网络模型。该模型利用深层图卷积学习情绪脑电全局通道间的内在关系,在卷积传播过程中应用残差连接和权重自映射解决深层图卷积网络面临的节点特征收敛到固定空间无法学习到有效特征的问题,并在卷积层后加入PN正则化扩大不同情绪特征间的距离,提高情绪识别的性能。在SEED数据集上进行实验,与浅层图卷积网络相比准确率提高了0.7%,标准差下降了3.15。结果表明该模型提取的全局脑区空间关联信息对情绪识别的有效性。

A Controlled Study of the Effectiveness of EEG Biofeedback Training on Children with Attention Deficit Hyperactivity Disorder

In order to study the treatment of the children with attention deficit hyperactivity disorder (ADHD), the integrated visual and auditory continuous performance test (IVA-CPT) was clinically applied to evaluate the effectiveness of electroencephalogram (EEG) biofeedback training. Of all the 60 children with ADHD aged more than 6 years, the effective rate of EEG biofeedback training was 91.6 % after 40 sessions of EEG biofeedback training. Before and after treatment by EEG biofeedback training, the overall indexes of IVA were significantly improved among predominately inattentive, hyperactive, and combined subtype of children with ADHD (P<0.001). It was suggested that EEG biofeedback training was an effective and vital treatment on children with ADHD.

Bedside ultrasound in the diagnosis of nonalcoholic fatty liver disease

Non-alcoholic fatty liver disease(NAFLD)is the most common liver disease in the United States.While the American Association for the Study of Liver Diseases guidelines define NAFLD as hepatic steatosis detected either on histology or imaging without a secondary cause of abnormal hepatic fat accumulation,no imaging modality is recommended as standard of care for screening or diagnosis.Bedside ultrasound has been evaluated as a non-invasive method of diagnosing NAFLD with the presence of characteristic sonographic findings.Prior studies suggest characteristic sonographic findings for NAFLD include bright hepatic echoes,increased hepatorenal echogenicity,vascular blurring of portal or hepatic vein and subcutaneous tissue thickness.These sonographic characteristics have not been shown to aid bedside clinicians easily identify potential cases of NAFLD.While sonographic findings such as attenuation of image,diffuse echogenicity,uniform heterogeneous liver,thick subcutaneous depth,and enlarged liver filling of the entire field could be identifiedby clinicians from bedside ultrasound.The accessibility,ease of use,and low-side effect profile of ultrasound make bedside ultrasound an appealing imaging modality in the detection of hepatic steatosis.When used with appropriate clinical risk factors and steatosis involves greater than 33%of the liver,ultrasound can reliably diagnose NAFLD.Despite the ability of ultrasound in detecting moderate hepatic steatosis,it cannot replace liver biopsy in staging the degree of fibrosis.The purpose of this review is to examine the diagnostic accuracy,utility,and limitations of ultrasound in the diagnosis of NAFLD and its potential use by clinicians in routine practices.

Predicting heat-stressed EEG spectra by self-organising feature map and learning vector quantizers——SOFM and LVQ based stress prediction

Self-Organising Feature Map (SOFM) along with learning vector quantizers (LVQ) have been designed to identify the alterations in brain electrical potentials due to exposure to high environmental heat in rats. Three groups of rats were considered—acute heat stressed, chronic heat stressed and control groups. After long EEG recordings following heat exposure, EEG data representing three different vigilance states such as slow wave sleep (SWS), rapid eye movement (REM) sleep and AWAKE were visually selected and further subdivided into 2 seconds long epoch. In order to evaluate the performance of artificial neural network (ANN) in recognizing chronic and acute effects of heat stress with respect to the control subjects, unsupervised learning algorithm was applied on EEG data. Mean performance of SOFM with quadratic taper function was found to be better (chronic-92.6%, acute-93.2%) over the other two tapers. The effect of LVQ after the initial SOFM training seems explicit giving rise to considerable improvements in performance in terms of selectivity and sensitivity. The percentage increase in selectivity with uniform taper function is maximum for chronic and its control group (4.01%) and minimum for acute group (1.29%) whereas, with Gaussian it is almost identical (chronic-2.57%, acute-2.03%, control- 2.33%). Quadratic taper function gives rise to an increase of 2.41% for chronic, 1.96% for acute and 2.91% for control patterns.

Cognitive control subprocess deficits and compensatory modulation mechanisms in patients with frontal lobe injury revealed by EEG markers:a basic study to guide brain stimulation

Background Frontal lobe injury(FLI)is related to cognitive control impairments,but the influences of FLI on the internal subprocesses of cognitive control remain unclear.Aims We sought to identify specific biomarkers for long-term dysfunction or compensatory modulation in different cognitive control subprocesses.Methods A retrospective case-control study was conducted.Event-related potentials(ERP),oscillations and functional connectivity were used to analyse electroencephalography(EEG)data from 12 patients with unilateral frontal lobe injury(UFLI),12 patients with bilateral frontal lobe injury(BFLI)and 26 healthy controls(HCs)during a Go/NoGo task,which included several subprocesses:perceptual processing,anticipatory preparation,conflict monitoring and response decision.Results Compared with the HC group,N2(the second negative peak in the averaged ERP waveform)latency,and frontal and parietal oscillations were decreased only in the BFLI group,whereas P3(the third positive peak in the averaged ERP waveform)amplitudes and sensorimotor oscillations were decreased in both patient groups.The functional connectivity of the four subprocesses was as follows:alpha connections of posterior networks in the BFLI group were lower than in the HC and UFLI groups,and these alpha connections were negatively correlated with neuropsychological tests.Theta connections of the dorsal frontoparietal network in the bilateral hemispheres of the BFLI group were lower than in the HC and UFLI groups,and these connections in the uninjured hemisphere of the UFLI group were higher than in the HC group,which were negatively correlated with behavioural performances.Delta and theta connections of the midfrontal-related networks in the BFLI group were lower than in the HC group.Theta across-network connections in the HC group were higher than in the BFLI group but lower than in the UFLI group.Conclusions The enhancement of low-frequency connections reflects compensatory mechanisms.In contrast,alpha connections are the opposite,therefore revealing more abnormal neural activity and less compensatory connectivity as the severity of injury increases.The nodes of the above networks may serve as stimulating targets for early treatment to restore corresponding functions.EEG biomarkers can measure neuromodulation effects in heterogeneous patients.

Evaluation of EEG β2/θ -ratio and channel locations in measuring anesthesia depth

In this paper, the ratio of powers in the frequency bands of β2 and θ waves in EEG signals (termed as the β2/θ -ratio) was introduced as a potential enhancement in measuring anesthesia depth. The β2/θ -ratio was compared to the relative β-ratio which had been commercially used in the BIS monitor. Sensitivity and reliability of the β2/θ -ratio and EEG measurement locations were analyzed for their effectiveness in measuring anesthesia depth during different stages of propofol induced anesthesia (awake, induction, maintenance, and emergence). The analysis indicated that 1) the relative β -ratio and β2/θ-ratio derived from the prefrontal, frontal, and the central cortex EEG signals were of substantial sensitivity for capturing anesthesia depth changes. 2) Certain channel positions in the frontal part of the cortex, such as , had the combined benefits of substantial sensitivity and noise resistance. 3) The β2/θ-ratio captured the initial excitation, while the relative β -ratio did not. 4) In the maintenance and emergence stages, the β2/θ -ratio showed improved reliability. Implications: The ratio of powers in EEG frequency bands and derived from the frontal cortex EEG channels has combined benefits of substantial sensitivity and noise resistance in measuring anesthesia depth.

The EEG Analysis of Auditory Emotional Stimuli Perception in TBI Patients with Different SCG Score

The electroencephalographic research has focused on the variety of responses to emotional auditory stimulation in patients at different stages after craniocerebral trauma. The patients sampling consisted of three groups: 13 comatose patients, 14 severe TBI patients, 12 moderate TBI patients, the control group consisting of the 28 healthy adults. The subjects were stimulated with auditory stimuli containing significant sounds (coughing, laughing, crying, bird singing, barking, scraping) and control sounds (white noise). We have analyzed statistically significant differences of power of the rhythmic activity registered during the presentation of different types of stimuli using Matlab. The t-test differences for each type of stimuli and the background were calculated as well as major ANOVA-effects. The results showed that EEG-response was based on the emotional stimuli valence, the consciousness levels, the severity of injury and the recovery process. The TBI patients showed lower theta-rhythm power in the frontal areas in response to the all emotional stimuli. The alpha-activity was reduced in the TBI patients: the alpha-rhythm depression was most vividly pronounced in the control group. The alpha-rhythm acceleration in the occipital areas was found only in the moderate TBI patients and only to the emotional stimuli. The severe TBI and comatose patients showed lower response rates to the neutral stimuli and higher response rates to the unpleasant physiological stimuli.

Psychophysiological Effects of Sideritis and Bacopa Extract and Three Combinations Thereof—A Quantitative EEG Study in Subjects Suffering from Mild Cognitive Impairment (MCI)

Mild cognitive impairment (MCI) is regarded as a transitional stage during the development of Alzheimer’s disease. Diagnosis of MCI can be obtained by the questionnaire “DemTect” in German speaking countries. Quantitative assessment has been successfully performed using psychometric testing concomitantly with quantitative EEG recording. The present investigation aimed at the possible treatment of MCI with two botanicals, namely extracts from Sideritis scardica (500 mg) or Bacopa monnieri (320 mg) and three combinations thereof using this method in order to find a new treatment. The performance of the d2-test, an arithmetic calculation test (CPT) and a memory-test revealed better performance for the d2-test only in the presence of Sideritis extract or the combinations with Bacopa extract. Quantitative EEG assessment during the different experimental conditions showed massive differences between both extracts. Whereas Sideritis extract and its combination with a low amount of Bacopa extract (160 mg) induced increases of spectral power in fronto-temporal brain areas, Bacopa and the combination of Sideritis with high amounts of Bacopa extract produced attenuation of all waves except for delta in fronto-temporal brain areas. These differences were also documented by quantitative EEG maps in comparison to Placebo. A different action of both extracts was confirmed by discriminant analysis, where Sideritis extract and its combination with low Bacopa grouped together quite at distance to Bacopa and the combination of Sideritis with high Bacopa. A combination of Sideritis extract with a low amount of Bacopa should be tested with daily repetitive dosing for at least 4 weeks as a consequence.

基于多脑区注意力机制胶囊融合网络的EEG-fNIRS情感识别

为了提高情感识别的准确率,提出多脑区注意力机制和胶囊融合模块的胶囊网络模型(MBA-CFc CapsNet).通过情感视频片段诱发采集EEG-fNIRS信号,构建TYUT3.0数据集.提取EEG和f NIRS的特征,将其映射到矩阵,通过多脑区注意力机制融合EEG和fNIRS的特征,给予不同脑区特征不同的权重,以提取质量更高的初级胶囊.使用胶囊融合模块,减少进入动态路由机制的胶囊数量,减少模型运行的时间.利用MBA-CFc CapsNet模型在TYUT3.0情感数据集上进行实验,与单模态EEG和f NIRS识别结果相比,2种信号结合情感识别的准确率提高了1.53%和14.35%.MBA-CF-cCapsNet模型与原始CapsNet模型相比,平均识别率提高了4.98%,与当前常用的CapsNet情感识别模型相比提高了1%~5%.

A Method for Quantifying the Emotional Intensity and Duration of a Startle Reaction with Customized Fractal Dimensions of EEG Signals

The assessment of emotions with fractal dimensions of EEG signals has been attempted before, but the quantification of the intensity and duration of sudden and short emotions remains a challenge. This paper suggests a method for this purpose, by using a new fractal dimension algorithm and by adjusting the amplitude of the EEG signal in order to obtain maximal separation of high and low fractal dimensions. The emotion was induced by embedding a scary image at 20 seconds in landscape videos of 60 seconds length. The new method did not only detect the onset of the emotion correctly, but also revealed its duration and intensity. The intensity is based on the magnitude and impulse of the fractal dimension signal. It is also shown that Higuchi’s method does not always detect emotion spikes correctly;on the contrary, the region of the expected emotional response can be represented by fractal dimensions smaller than the rest of the signal, whereas the new method directly reveals distinct spikes. The duration of these spikes was 10 - 11 seconds. The magnitude of these spikes varied across the EEG channels. The build-up and cool-down of the emotions can occur with steep and flat gradients.

15 Years of Evolution of Non-Invasive EEG-Based Methods for Restoring Hand &Arm Function with Motor Neuroprosthetics in Individuals with High Spinal Cord Injury: A Review of Graz BCI Research

Patients who suffer from a high spinal cord injury have severe motor disabilities in the lower as well as in the upper extremities. Thus they rely on the help of other people in everyday life. Restoring the function of the upper limbs, especially the grasp function can help them to gain some independence. Using EEG-based neuroprosthetics is a way to help tetraplegic people restore different grasp types as well as moving the arm and the elbow. In this work an overview of non-invasive EEG-based methods for restoring the hand and arm function with the use of neuroprosthetics in individuals with high spinal cord injury is given. Since the Graz BCI group is leading in this area of non-invasive research mainly, the work of this group is represented.

EFFECT OF ELECTROACUPUNCTURE OF ACUPOINTS OF THE HEART MERIDIAN ON ECG, SMALL INTESTINAL ELECTROGRAM AND EEG IN THE RABBIT WITH MYOCARDIAL ISCHEMIA

In the present paper, effects of electroacupuncture (EA) of 3 points of the Heart Meridian and other 3 points of the Lung Meridian on changes of electrocardiogram (ECG), small intestinal electrogram (SIG) and electroencephalogram (EEG) in intravenous drip of pituitrin induced myocardial ischemia rabbits. The three points of the Heart Meridian are "Shenmen" (HT 7), "Lingdao" (HT 4) and one point between HT 7 and HT 4, the 3 points of the Lung Meridian are "Taiyuan"(LU 9), Lieque (LU 7) and one point between LU 9 and LU 7. These points are punctured with filiform needles and stimulated electrically by setting the parameters being frequency of 2.5 Hz, dense sparse waves and duration of 10 min. Results display that the regulative effect of EA of the Heart Meridian is superior to that of EA of the Lung Meridian on the three indexes, showing a closer correlation between the whole Heart Meridian and activities of ECG, SIG and EEG.

EnkephaloVision: Anatomical Functionality Indicated by Ultrashort Transient Regional EEG Spectral Power Changes during Cognitive and Emotional Challenges

Anatomical functionality is a major topic in brain research. Numerous investigations have shown task dependent activation of focal brain areas, with most information based on time-averaged data due to methodological limitations. Ultra-fast quantitative EEG, especially in the newly developed combination with eye tracking (EnkephaloVision), is very suitable to follow activities of local electric circuits. This investigation in 57 subjects revealed transient focal frequency changes reaching up to more than 6000% of global median spectra power during cognitive and emotional challenges at frontal electrode positions. Recording epochs of 364 ms uncovered coherences with respect to focal brain areas and single frequencies, which are typically lost during averaged calculations. When averaging data over a whole scene, a least demanding challenge like viewing a boring animal video only activated the lateral frontal lobe, whereas solving brain-teasers and performance of mathematical calculations led to delta (modulated by acetylcholine) and theta (modulated by norepinephrine) increases in all brain regions in a statistically significant manner. In addition to delta and theta increases, performance of the Stroop test led to beta2 (related to GABA-ergic transmission) increases in the temporal lobe. The higher the mental demand the more brain regions were involved during 10 different challenges. There was no challenge which did not activate the lateral frontal brain in terms of increases of delta and theta spectral power. The results are in line with the view that the lateral frontal lobe is involved primarily during cognitive and emotional behavior related to activity changes of acetylcholine and norepinephrine.

基于深度学习的EEG数据分析技术综述

对近年来的相关工作进行全面分析、横向比较,梳理出基于深度学习的EEG数据分析闭环流程.对EEG数据进行介绍,从深度学习在EEG数据预处理、特征提取以及模型泛化3个关键阶段的应用进行展开,梳理深度学习算法在相应阶段提供的研究思路和解决方案,包括各阶段所存在的难点与问题.全方位总结出不同算法的主要贡献和局限性,讨论深度学习技术在各个阶段处理EEG数据时所面临的挑战及未来的发展方向.