This method effects excellently in the analysis of EEG signals.
该方法在脑电信号分析中取得了很好的成效。
The classification accuracy of experiment EEG signals reach 89%.
对真实脑电数据的分类正确率达到89%。
Several types of EEG signals have been adopted in EEG based BCI.
基于脑电的脑—机接口采用了很多种类型的脑电信号。
A new method for detecting epileptic spikes from EEG signals is presented in this paper.
本文提出了一种新的检测癫痫eeg棘波的方法。
Also, an adaptive filter is employed to separate steady and unsteady conponets from original EEG signals.
同时，使用自适应滤波器对原始信号进行滤波；
Finally, the fuzzy similarity index is applied to indicate the preictal state of nine rats with EEG signals.
最后，分析大鼠癫痫EEG信号，检测癫痫发作前期状态。
Ar model based distance measurements with EEG signals are well reliable for the injury detection of the central nervous system.
基于AR模型的EEG信号距离测度方法可以较好地表征中枢神经系统损伤的情况。
A high accuracy BCI is designed using electroencephalogram EEG signals where the subjects have to think of only a single mental task.
设计一种仅使用进行简单思维任务时脑电信号(脑电图)的高准确率脑机接口。
An algorithm was designed to sort the headset EEG signals into either meditation or attention inputs, each with their own distinct pattern.
编码团队设计了一种算法，把耳机采集到的脑电图信号分为沉思和关注两类。
They found that, from the EEG signals alone, they could deduce which movement this patient had been instructed to imagine with 100% accuracy.
他们发现，光是从EEG信号他们就可以以100%的准确率推断出这位病人被指示想象那些动作。
ECG artifact and power noise are successfully removed from the origanal EEG signal with the ICA method with no harm to the details of EEG signals.
利用ICA方法对实测脑电信号中的心电伪迹和工频噪声进行了消除，成功去除噪声并保留脑电信号的特征不变。
Based on the EEG signal-processing system applying bispectral analysis, the results and their analysis obtained by processing EEG signals are given.
在研制脑电信号双谱分析处理系统软件及硬件的基础上，给出了对实际脑电信号处理所得到的实验结果及分析。
However, the spontaneous EEG signals are very weak, noisy, and non-stationary signal, so efficient methods of EEG analysis is the core of BCI system.
然而，自发脑电信号非常弱，噪声大，而且是非平稳信号，因此合适的脑电信号分析研究方法是BCI系统的核心内容。
By using these methods, the system can be of the feature of zero phase error, and the filtering of EEG signals with zero phase error can be realized.
利用该方法可以使系统具有零相位特性，实现脑电信号的零相位失真滤波。
The application of gray model in feature extraction of spontaneous EEG signals is studied and the overall scheme of EEG feature extraction is presented.
研究了灰色模型在自发脑电特征提取中的应用，同时给出了脑电信号特征提取的总体方案。
The EEG signals were obviously restrained when magnetic stimulate on acupoint of Shenmen(HT7), having the same effect of adjust neural function as that to acupuncture.
实验表明，对人体神门穴进行磁刺激对脑电信号有明显抑制，与进行针刺或电刺激同样具有调节神经机能的作用。
A novel method of EEG signals compression representation and epileptiform spikes recognition based on wavelet neural network and its algorithm is presented in this paper.
本文在对小波神经网络及其算法研究的基础上，提出了一种对脑电信号压缩表达和痫样脑电棘波识别的新方法。
EEG signals are very weak, generally accompanied by strong background noises, but they reflect various physiological phenomena and make great sense in the clinical condition.
脑电信号本身很微弱、并伴有很强的背景噪声，但其中蕴藏着多种生理现象，有着非常重要的临床价值。
Seeking for new BCI modalities, which can significant enhance both endogenous and exogenous components in recorded EEG signals is of great importance in BCI system development.
寻找新的脑-机接口模式使之能显著提升记录脑电信号中的内源性与外源性成分在脑-机接口研究中具有重要意义。
Based on the characteristics of the specific thinking-evoked EEG signals, an approach is proposed to determine their distribution and pick up their waveform out of strong noises.
针对特定思维诱发脑电信号的特点，提出一种确定其分布情况及提取其波形的方法。
A wealth of brain information is provided in EEG signals. Some characteristic parameters can be extracted for representing different cerebral function states by careful analyses and processing.
脑电信号蕴含着丰富的大脑活动信息，通过对脑电信号的有效分析和处理，可以从中提取出可靠的特征参量来反映不同的脑功能状态。
EEG signals have a large amount of physiology and pathology information, electrical activity of the brain plays a very important role in the field of the related disease of sleep and brain science.
脑电信号种包含大量的生理和病理信息，在睡眠相关疾患和脑科学研究中起着非常重要的作用。
Researchers used a portable electroencephalography (EEG) device to record electrical signals from the brains of 16 patients diagnosed as being in a vegetative state.
研究人员使用携带型脑电图仪记录了16名被诊断为处于植物人状态的患者大脑中传来的电子信号。
Scientists used a technique called electroencephalograhy (EEG) to analyse the drivers' brain signals.
科学家利用称之为脑电图的技术来分析司机的脑电波信号。
Researchers use EEG to measure electrical activity along a person's scalp. These electrical signals can move a computer cursor, play video games and perform other two-dimensional tasks.
研究人员通过脑电图来测量人体头皮上的电荷活动，通过这些电信号，可以移动鼠标光标，玩视频游戏以及完成其他的二维操作。
"Using eeg to send tweet," he wrote, referring to the electroencephalograph he used to record electrical signals in his brain.
他所写的“用脑电图发送邮件，”其实指的是他用脑电图仪记录其大脑的电信号并发送出去。
With the resulting EEG and EMG data, the researchers were able to identify signals that occurred consistently during emergency brake response situations.
根据脑电图和肌电图给出的数据，研究人员能够鉴别在紧急制动反应测试中发出的电信号。
Researchers % used a portable electroencephalography (EEG) device to record electrical signals from the brains of 16 patients diagnosed as being in a vegetative state.
研究人员使用便携式脑电图仪记录了16名被诊断为处于植物人状态的患者大脑中传来的电子信号。
The electroencephalogram(EEG) is one of the most important bio-electric signals of the human. Now many people pay much attention to the therapy effects through monitoring the EEG.
脑电信号（EEG）是人体重要的生物电信号，目前关于脑电信号监测在某些疾病患者治疗过程中的作用得到医疗机构越来越广泛的重视。
The second task of brain signal analysis is to extract EP signals from spontaneous EEG in strong backgrounds.
脑电信号分析的任务之二就是如何从强背景自发eeg中提取ep信号。
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