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In order to sufficiently exploit the advantages of different signal processing methods, such as wavelet transformation (WT), artificial neural networks (ANN) and expert rules (ER), a synthesized multi-method was introduced to detect and classify the epileptic waves in the EEG data. Using this method, at first, the epileptic waves were detected from pre-processed EEG data at different scales by WT, then the characteristic parameters of the chosen candidates of epileptic waves were extracted and sent into the well-trained ANN to identify and classify the true epileptic waves,and at last, the detected epileptic waves were certificated by ER. The statistic results of detection and classification show that, the synthesized multi-method has a good capacity to extract signal features and to shield the signals from the random noise. This method is especially fit for the analysis of the biomedical signals in biomedical engineering which are usually non-placid and nonlinear. 相似文献
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In order to investigate the characteristics of sensorimotor cortex during motor execution(ME), voluntary, stimulated and imaginary finger flexions were performed by ten volunteer subjects. Electroencephalogram(EEG) data were recorded according to the modified 10-20 International EEG System. The patterns were compared by the analysis of the motion-evoked EEG signals focusing on the contralateral(C3) and ipsilateral(C4) channels for hemispheric differences. The EEG energy distributions at alpha(8—13 Hz), beta(14—30 Hz) and gamma(30—50 Hz) bands were computed by wavelet transform(WT) and compared by the analysis of variance(ANOVA). The timefrequency(TF) analysis indicated that there existed a contralateral dominance of alpha post-movement event-related synchronization(ERS) pattern during the voluntary task, and that the energy of alpha band increased in the ipsilateral area during the stimulated(median nerve of wrist) task. Besides, the contralateral alpha and beta event-related desynchronization(ERD) patterns were observed in both stimulated and imaginary tasks. Another significant difference was found in the mean power values of gamma band(p0.01)between the imaginary and other tasks. The results show that significant hemispheric differences such as alpha and beta band EEG energy distributions and TF changing phenomena(ERS/ERD) were found between C3 and C4 areas during all of the three patterns. The largest energy distribution was always at the alpha band for each task. 相似文献
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Team Work:培养创新能力和团队精神的好形式 总被引：6，自引：1，他引：6
与国外教育相比，国内教育在严谨书本知识和系统理论知识教育方面并不弱，但在创新及实践能力培养方面尚有较大的差距。即使在天津大学这样的工科院校中，也存在重理论、轻实验，重软件、轻硬件和好高骛远、不愿承受艰苦细致的基本技术训练的倾向，这样，培养的学生就难免高分低能。对此，必须进行改革。 相似文献
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为解决传统可见光成像在步态信息检测与身份识别中存在的诸多问题,提出了利用人体红外辐射成像及身份认证的新方法。首先将人体自身辐射的红外光转换为红外热图像,然后分割人体目标并将目标轮廓归一化,同时将轮廓序列叠加以获取红外信息能量图,再对其进行小波分解;提取红外信息能量图分解后的边界矩参数及骨架特征参数,以此作为特征参量输入支持向量机进行身份识别,正确识别率（PCR）为78%～91%,且识别效果不受人体携带外物（如背包、抱球）的影响,仅受衣着的影响较大。研究表明：基于人体红外辐射的身份识别有利于人体目标检测与精确描述。 相似文献
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The classification of pathological voice from healthy voice was studied based upon 27 acoustic features derived from a single sound signal of vowel /a:/. First, the feature space was transferred to reduce the data dimension by principle component analysis (PCA). Then the voice samples were classified according to the reduced PCA parameters by support vector machine (SVM) using radial basis function (RBF) as a kernel function. Meanwhile, by changing the ratio of opposite class samples, the accuracy under different features combinations was tested. Experimental data were provided by the voice database of Massachusetts Eye and Ear Infirmary (MEEI) in which 216 vowel /a:/ samples were collected from subjects of healthy and pathological cases, and tested with 5 fold cross-validation method. The result shows the positive rate of pathological voices was improved from 92% to 98% through the PCA method. STD, Fatr, Tasm, NHR, SEG, and PER are pathology sensitive features in illness detection. Using these sensitive features the accuracy of detection of pathological voice from healthy voice can reach 97%. 相似文献
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A brain-computer interface （BCI） -based electric wheelchair control system was developed, which enables the users to move the wheelchair forward or backward, and turn left or right without any pre-learning. This control system makes use of the amplitude enhancement of alpha-wave blocking in electroencephalogram （EEG） when eyes close for more than 1 s to constitute a BCI for the switch control of wheelchair movements. The system was formed by BCI control panel, data acquisition, signal processing unit and interface control circuit. Eight volunteers participated in the wheelchair control experiments according to the preset routes. The experimental results show that the mean success control rate of all the subjects was 81.3%, with the highest reaching 93.7%. When one subject＇s triggering time was 2.8 s, i.e., the flashing time of each cycle light was 2.8 s, the average information transfer rate was 8.10 bit/min, with the highest reaching 12.54 bit/min. 相似文献
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Feature extraction of electrocardiogram(ECG) is oneof the mostimportanttasksin heart disease diagnosis .Gen-erally,these algorithms include length and energytransfor-mation[1],hidden Markov models[2],neural networks[3],and wavelet transform[4], etc . Howe… 相似文献
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基于P300的脑机接口系统研究 总被引：3，自引：0，他引：3
设计了Oddball刺激程序及诱发电位P300实验方案，对实验所采集到的含有诱发电位信号的EEG数据进行了预处理和模式识别方法的研究，初步建立了基于诱发电位P300的BCI系统的信号采集与处理模型，分别利用小波变换、相干平均方法对P300信号进行提取，尤其是诱发电位的少次提取对实现实时BCI系统具有重要意义，为将来实现基于诱发电位P300的实时BCI系统打下了坚实的基础。 相似文献
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