Based on the good localization characteristic of the wavelet transform both in time and frequency domain, a de-noising method based on wavelet transform is presented, which can make the extraction of visual evoked pot...Based on the good localization characteristic of the wavelet transform both in time and frequency domain, a de-noising method based on wavelet transform is presented, which can make the extraction of visual evoked potentials in single training sample from the EEG background noise in favor of studying the changes between the single sample response happen. The information is probably related with the different function, appearance and pathologies of the brain. At the same time this method can also be used to remove those signal’s artifacts that do not appear with EP within the same scope of time or frequency. The traditional Fourier filter can hardly attain the similar result. This method is different from other wavelet de-noising methods in which different criteria are employed in choosing wavelet coefficient. It has a biggest virtue of noting the differences among the single training sample and making use of the characteristics of high time frequency resolution to reduce the effect of interference factors to a maximum extent within the time scope that EP appear. The experiment result proves that this method is not restricted by the signal-to-noise ratio of evoked potential and electroencephalograph (EEG) and even can recognize instantaneous event under the condition of lower signal-to-noise ratio, as well as recognize the samples which evoked evident response more easily. Therefore, more evident average evoked response could be achieved by de-nosing the signals obtained through averaging out the samples that can evoke evident responses than de-nosing the average of original signals. In addition, averaging methodology can dramatically reduce the number of record samples needed, thus avoiding the effect of behavior change during the recording process. This methodology pays attention to the differences among single training sample and also accomplishes the extraction of visual evoked potentials from single trainings sample. As a result, system speed and accuracy could be improved to a great extent if this methodology is applied to brain-computer interface system based on evoked responses.展开更多
AIM： To detect the relationship between infusion pressure and postoperative ganglion cells function.METHODS： This prospective observational cohort study included sixty-one eyes that underwent uncomplicated cataract ...AIM： To detect the relationship between infusion pressure and postoperative ganglion cells function.METHODS： This prospective observational cohort study included sixty-one eyes that underwent uncomplicated cataract surgery. Patients were divided into two groups according to infusion time（IT） recorded using surgery equipment [Group A： IT〉IT_（mean）（27 eyes）; Group B： IT展开更多
分析兔皮层体感诱发电位的时域和频域特性。兔麻醉开颅,从大脑体感运动皮层引导诱发电位。连续多次刺激,以3 800 H z采样率采样。测量每次诱发电位各个波形成分的峰潜伏期。分析诱发电位的功率谱。比较单次和叠加平均电位的时频特性。...分析兔皮层体感诱发电位的时域和频域特性。兔麻醉开颅,从大脑体感运动皮层引导诱发电位。连续多次刺激,以3 800 H z采样率采样。测量每次诱发电位各个波形成分的峰潜伏期。分析诱发电位的功率谱。比较单次和叠加平均电位的时频特性。结果显示诱发成分时域变异性在一个刺激周期内随时间逐渐增大,诱发电位的频谱包括3个主要频谱包。叠加平均技术使信号产生波形融合,新波形产生,后发放成份消失等多种畸变。展开更多
文摘Based on the good localization characteristic of the wavelet transform both in time and frequency domain, a de-noising method based on wavelet transform is presented, which can make the extraction of visual evoked potentials in single training sample from the EEG background noise in favor of studying the changes between the single sample response happen. The information is probably related with the different function, appearance and pathologies of the brain. At the same time this method can also be used to remove those signal’s artifacts that do not appear with EP within the same scope of time or frequency. The traditional Fourier filter can hardly attain the similar result. This method is different from other wavelet de-noising methods in which different criteria are employed in choosing wavelet coefficient. It has a biggest virtue of noting the differences among the single training sample and making use of the characteristics of high time frequency resolution to reduce the effect of interference factors to a maximum extent within the time scope that EP appear. The experiment result proves that this method is not restricted by the signal-to-noise ratio of evoked potential and electroencephalograph (EEG) and even can recognize instantaneous event under the condition of lower signal-to-noise ratio, as well as recognize the samples which evoked evident response more easily. Therefore, more evident average evoked response could be achieved by de-nosing the signals obtained through averaging out the samples that can evoke evident responses than de-nosing the average of original signals. In addition, averaging methodology can dramatically reduce the number of record samples needed, thus avoiding the effect of behavior change during the recording process. This methodology pays attention to the differences among single training sample and also accomplishes the extraction of visual evoked potentials from single trainings sample. As a result, system speed and accuracy could be improved to a great extent if this methodology is applied to brain-computer interface system based on evoked responses.
基金Supported by the Beijing Municipal Commission of Science and Technology(No.Z151100004015073)
文摘AIM： To detect the relationship between infusion pressure and postoperative ganglion cells function.METHODS： This prospective observational cohort study included sixty-one eyes that underwent uncomplicated cataract surgery. Patients were divided into two groups according to infusion time（IT） recorded using surgery equipment [Group A： IT〉IT_（mean）（27 eyes）; Group B： IT
文摘分析兔皮层体感诱发电位的时域和频域特性。兔麻醉开颅,从大脑体感运动皮层引导诱发电位。连续多次刺激,以3 800 H z采样率采样。测量每次诱发电位各个波形成分的峰潜伏期。分析诱发电位的功率谱。比较单次和叠加平均电位的时频特性。结果显示诱发成分时域变异性在一个刺激周期内随时间逐渐增大,诱发电位的频谱包括3个主要频谱包。叠加平均技术使信号产生波形融合,新波形产生,后发放成份消失等多种畸变。
