Steady-state flsash visual evoked potentials (SFVEPs) of 30 Hz were recorded for 46 normal subjects (89 eyes )and 35 patients (51 eyes )with optic neuropathy. The visual acuities of 58.8%affected eyes were less than 0.1. The recorded waveforms were analyzed by discrete Foruier transform (DTF). The amplitudes and phases of fundamental response component and second harmonic were abstracted as characteristic values of the waveform.The total abnormal ratio was 80. 4%. The abnormal types showed the reduced amplitudes,reduced amplitude with phase change, the phases changes, and flat wave. The advantages of SFVEPs in clinical application were discussed. （Chin J Ocul Fundus Dis,1994,10:213-215）
We proposed a multi-resolution-wavelet-transform based method to extract brainstem auditory evoked potential (BAEP) from the background noise and then to identify its characteristics correctly. Firstly we discussed the mother wavelet and wavelet transform algorithm and proved that bi-orthogonal wavelet bior5.5 and stationary discrete wavelet transform (SWT) were more suitable for BAEP signals. The correlation analysis of D6 scale wavelet coefficients between single trails and the ensemble average of all trails showed that the trails with good correlation (> 0.4) had higher signal-to-noise ratio, so that we could get a clear BAEP from a few trails by an average and wavelet filter method. Finally, we used this method to select desirable trails, extracted BAEP from every 10 trails and calculated theⅠ-Ⅴinter-waves' latency. The results showed that this strategy of trail selection was efficient. This method can not only achieve better de-noising effect, but also greatly reduce the stimulation time needed as well.
Motor imaging therapy is of great significance to the rehabilitation of patients with stroke or motor dysfunction, but there are few studies on lower limb motor imagination. When electrical stimulation is applied to the posterior tibial nerve of the ankle, the steady-state somatosensory evoked potentials (SSSEP) can be induced at the electrical stimulation frequency. In order to better realize the classification of lower extremity motor imagination, improve the classification effect, and enrich the instruction set of lower extremity motor imagination, this paper designs two experimental paradigms: Motor imaging (MI) paradigm and Hybrid paradigm. The Hybrid paradigm contains electrical stimulation assistance. Ten healthy college students were recruited to complete the unilateral movement imagination task of left and right foot in two paradigms. Through time-frequency analysis and classification accuracy analysis, it is found that compared with MI paradigm, Hybrid paradigm could get obvious SSSEP and ERD features. The average classification accuracy of subjects in the Hybrid paradigm was 78.61%, which was obviously higher than the MI paradigm. It proves that electrical stimulation has a positive role in promoting the classification training of lower limb motor imagination.
The maximum length sequence (m-sequence) has been successfully used to study the linear/nonlinear components of auditory evoked potential (AEP) with rapid stimulation. However, more study is needed to evaluate the effect of the m-sequence order in terms of the noise attenuation performance. This study aimed to address this issue using response-free electroencephalogram (EEG) and EEGs with nonlinear AEPs. We examined the noise attenuation ratios to evaluate the noise variation for the calculations of superimposed averaging and cross-correlation, respectively, which constitutes the main process in the deconvolution method using the dataset of spontaneous EEGs to simulate the cases of different orders (order 5 to 12) of m-sequences. And an experiment using m-sequences of order 7 and 9 was performed in true cases with substantial linear and nonlinear AEPs. The results demonstrate that the noise attenuation ratio is well agreed with the theoretical value derived from the properties of m-sequences on the random noise condition. The comparison of waveforms for AEP components from two m-sequences showed high similarity suggesting the insensitivity of AEP to the m-sequence order. This study provides a more comprehensive solution to the selection of m-sequences which will facilitate the feasible application on the nonlinear AEP with m-sequence method.
Brain-computer interface (BCI) has great potential to replace lost upper limb function. Thus, there has been great interest in the development of BCI-controlled robotic arm. However, few studies have attempted to use noninvasive electroencephalography (EEG)-based BCI to achieve high-level control of a robotic arm. In this paper, a high-level control architecture combining augmented reality (AR) BCI and computer vision was designed to control a robotic arm for performing a pick and place task. A steady-state visual evoked potential (SSVEP)-based BCI paradigm was adopted to realize the BCI system. Microsoft's HoloLens was used to build an AR environment and served as the visual stimulator for eliciting SSVEPs. The proposed AR-BCI was used to select the objects that need to be operated by the robotic arm. The computer vision was responsible for providing the location, color and shape information of the objects. According to the outputs of the AR-BCI and computer vision, the robotic arm could autonomously pick the object and place it to specific location. Online results of 11 healthy subjects showed that the average classification accuracy of the proposed system was 91.41%. These results verified the feasibility of combing AR, BCI and computer vision to control a robotic arm, and are expected to provide new ideas for innovative robotic arm control approaches.
We have utilized the binocular flat and stereoscopic pattern to record visual evoked potentials (VEP) in normal and strabismic subjects. The aim was to find an electrophysiological correlation with the degree of binocular interaction in these subjects.The perception as tridimensional or flat derived from the disparity obtained with polaroid filters placed in front of the eyes. In normal subjects, the results demonstrated a significant increase of VEP amplitude during tridimensional perception of the pattern. In strabismic subjects the electrophysiological response were not correlated with the binocular conditions. The findings in the present study suggest that the binocular disparity in VEP examination is a useful technique and a better objective index for evaluating stereoscopic function than the psychophysical technique. （Chin J Ocul Fundus Dis,1992,8:10-13）
High-frequency steady-state asymmetric visual evoked potential (SSaVEP) provides a new paradigm for designing comfortable and practical brain-computer interface (BCI) systems. However, due to the weak amplitude and strong noise of high-frequency signals, it is of great significance to study how to enhance their signal features. In this study, a 30 Hz high-frequency visual stimulus was used, and the peripheral visual field was equally divided into eight annular sectors. Eight kinds of annular sector pairs were selected based on the mapping relationship of visual space onto the primary visual cortex (V1), and three phases (in-phase[0º, 0º], anti-phase [0º, 180º], and anti-phase [180º, 0º]) were designed for each annular sector pair to explore response intensity and signal-to-noise ratio under phase modulation. A total of 8 healthy subjects were recruited in the experiment. The results showed that three annular sector pairs exhibited significant differences in SSaVEP features under phase modulation at 30 Hz high-frequency stimulation. And the spatial feature analysis showed that the two types of features of the annular sector pair in the lower visual field were significantly higher than those in the upper visual field. This study further used the filter bank and ensemble task-related component analysis to calculate the classification accuracy of annular sector pairs under three-phase modulations, and the average accuracy was up to 91.5%, which proved that the phase-modulated SSaVEP features could be used to encode high- frequency SSaVEP. In summary, the results of this study provide new ideas for enhancing the features of high-frequency SSaVEP signals and expanding the instruction set of the traditional steady state visual evoked potential paradigm.
ObjectiveTo explore changes on Electroencephalograph (EEG) and Evoked Potential (EP) changes in autoimmune encephalitis.MethodsEight cases with autoimmune encephalitis from Sichuan people's hospital during July 18th 2014 to July 18th 2016 were recruited. The inclusion criteria included:① The blood and cerebral spinal fluid (CSF) of patients were sent to Neurology Lab of Peking Union Medical College Hospital for autoimmunerelated antibody analysis and confirmed as autoimmune encephalitis.2 Patient had done at least 2 or more times of routine EEG or video EEG (VEEG). 1 or more times of auditory brainstem response (ABR), Visual evoked potential (VEP) and Somatosensory evoked potential (SEP) for both upper and lower limbs. 3 Patients had classical clinical manifestation of autoimmune encephalitis as abnormal psychomotor behaviors, seizures, memory loss, fever, headache, and even disturbance of consciousness or decreased ventilate function.ResulstOf 8 patients in this study, 5 were anti NMDA-R encephalitis, 2 were anti GABABR encephalitis, and 1 was positive for both antibodies. The EEG profile of 5 anti NMDA-R encephalitis:2 of them had β wave in early stage (about 10th day) and δ wave with fast wave even appeared as δ brush in middle stage (about 20th day). They all had severe symptoms and long hospitalization but negative MRI. Another 2 of them could be seen sparsely distributed sharp wave and sharp-slow wave in their EEG. Their EEG gradually turned to normal when their symptoms gradually disappeared. The last one had normal EEG during the whole disease course. The EEG profile of anti GABAB-R encephalitis as following. 1 was dominant by slow wave and EEG went normal after effective treatment and the other showed generalized α wave especially α wave in frontal region. The latter patient withdraw treatment. For the only 1 both antibodies positive patient, EEG showed slow wave and it turned to normal when symptoms disappeared. EP showed some abnormalities with wave amplitude and latency changes in some patients.EP (SEP、VEP) turned to normal when symptoms disappeared.ConclusionThe EEG present differently in different types of autoimmune encephalitis and change with stages of disease. EEG may be used as an indicator for prognosis as well. When EEG shows fast wave with the history of patient points to encephalitis, blood and CSF antibodies for NMDA-R should be checked routinely. Generalized α wave on EEG should also be an indicator for checking GABAB-R. More researches should be done for EP changes in autoimmune encephalitis for our study was based on a small patient number.
Brain computer interface is a control system between brain and outside devices by transforming electroencephalogram (EEG) signal. The brain computer interface system does not depend on the normal output pathways, such as peripheral nerve and muscle tissue, so it can provide a new way of the communication control for paralysis or nerve muscle damaged disabled persons. Steady state visual evoked potential (SSVEP) is one of non-invasive EEG signals, and it has been widely used in research in recent years. SSVEP is a kind of rhythmic brain activity simulated by continuous visual stimuli. SSVEP frequency is composed of a fixed visual stimulation frequency and its harmonic frequencies. The two-dimensional ensemble empirical mode decomposition (2D-EEMD) is an improved algorithm of the classical empirical mode decomposition (EMD) algorithm which extended the decomposition to two-dimensional direction. 2D-EEMD has been widely used in ocean hurricane, nuclear magnetic resonance imaging (MRI), Lena image and other related image processing fields. The present study shown in this paper initiatively applies 2D-EEMD to SSVEP. The decomposition, the 2-D picture of intrinsic mode function (IMF), can show the SSVEP frequency clearly. The SSVEP IMFs which had filtered noise and artifacts were mapped into the head picture to reflect the time changing trend of brain responding visual stimuli, and to reflect responding intension based on different brain regions. The results showed that the occipital region had the strongest response. Finally, this study used short-time Fourier transform (STFT) to detect SSVEP frequency of the 2D-EEMD reconstructed signal, and the accuracy rate increased by 16%.
Injury of dorsal root ganglia (DRG) may cause sensory and motor dysfunction. In order to investigate the changes of somato-sensory evoked potential (SEP) and histological characteristics of DRG in different causes and different periods of injury, fifty-two rabbits were chosed to build the models. The rabbits were divided into 4 groups: Control group (n = 4); mechanical compressing group (n = 16); inflammatory injury group (n = 16); and treatment group (2% lidocaine with hydroprednisone was administered locally, n = 16). After one to eight weeks, SEP was determined and samples of DRG were obtained to observe the histological and ultrastructural changes every week. The result showed that the gap junction of microvascular endothelium in DRG had been destroyed by the mechanical compression was the major cause of the vessel permeability increasing. The increasing of endothelial pinocytic vesicles transportation and widening of endothelial gap junction were the main causes of inflammatory irritation of DRG. The local infiltration with 2% lidocaine and hydroprednisone could obviously ameliorate inflammatory injury in DRG.