Pub Date : 2005-05-26DOI: 10.1109/ICNIC.2005.1499837
Wang Yijun, W. Ruiping, G. Xiaorong, G. Shangkai
Low-frequency steady-state visual evoked potentials (SSVEPs) are used as the input signal in the present SSVEP-based brain-computer interface (BCI). This prototype system has a high information transfer rate. On the other hand, it has some limitations including visual fatigue, false positive, and some possibility of causing a seizure. These drawbacks can be largely eliminated when using high-frequency stimulations. In this paper, we study the amplitude versus stimulation frequency response of SSVEPs. The signal-to-noise ratio versus frequency curve suggests that the high-frequency SSVEP (>20Hz) could help to construct a practical BCI system.
{"title":"Brain-computer interface based on the high-frequency steady-state visual evoked potential","authors":"Wang Yijun, W. Ruiping, G. Xiaorong, G. Shangkai","doi":"10.1109/ICNIC.2005.1499837","DOIUrl":"https://doi.org/10.1109/ICNIC.2005.1499837","url":null,"abstract":"Low-frequency steady-state visual evoked potentials (SSVEPs) are used as the input signal in the present SSVEP-based brain-computer interface (BCI). This prototype system has a high information transfer rate. On the other hand, it has some limitations including visual fatigue, false positive, and some possibility of causing a seizure. These drawbacks can be largely eliminated when using high-frequency stimulations. In this paper, we study the amplitude versus stimulation frequency response of SSVEPs. The signal-to-noise ratio versus frequency curve suggests that the high-frequency SSVEP (>20Hz) could help to construct a practical BCI system.","PeriodicalId":169717,"journal":{"name":"Proceedings. 2005 First International Conference on Neural Interface and Control, 2005.","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134343389","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2005-05-26DOI: 10.1109/ICNIC.2005.1499834
Pei Weihua, Chen Hongda, Tang Jun, Lu Lin, Liu Jin-bin, Su Xiaohong, Wu Huijuan, Huo Xiaofeng, C. Jinghua, L. Xiaoxin, Li Kai
The present study reports a subretinal implant device which can imitate the function of photoreceptor cells. Photodiode (PD) arrays on the chip translate the incident light into current according to the intensity of light. With an electrode at the end of every photodiode, the PDs transfer the current to the remnant healthy visual cells such as bipolar cells and horizontal cells and then activate these cells. Biocompatible character of the materials and artificial photoreceptor itself were tested and the photoelectric characteristics of the chips in simulative condition were described and discussed.
{"title":"Subretinal implantable artificial photoreceptor","authors":"Pei Weihua, Chen Hongda, Tang Jun, Lu Lin, Liu Jin-bin, Su Xiaohong, Wu Huijuan, Huo Xiaofeng, C. Jinghua, L. Xiaoxin, Li Kai","doi":"10.1109/ICNIC.2005.1499834","DOIUrl":"https://doi.org/10.1109/ICNIC.2005.1499834","url":null,"abstract":"The present study reports a subretinal implant device which can imitate the function of photoreceptor cells. Photodiode (PD) arrays on the chip translate the incident light into current according to the intensity of light. With an electrode at the end of every photodiode, the PDs transfer the current to the remnant healthy visual cells such as bipolar cells and horizontal cells and then activate these cells. Biocompatible character of the materials and artificial photoreceptor itself were tested and the photoelectric characteristics of the chips in simulative condition were described and discussed.","PeriodicalId":169717,"journal":{"name":"Proceedings. 2005 First International Conference on Neural Interface and Control, 2005.","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133442559","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2005-05-26DOI: 10.1109/ICNIC.2005.1499851
Yang Yuankui, Z. Jianzhong
Electroencephalography (EEG) is widely used to record activities of human brain in the area of psychology for many years. With the development of technology, neural basis of functional areas of emotion processing is revealed gradually. In order to extract the useful information of emotion from the background of EEG signals and noise, we propose to combine methods of psychology and the technology of signal processing such as pattern recognition, etc. In this paper, we first review the psychological methods and signal processing technology in the field of emotion research, and point out the junctions of these two approaches. Secondly, we introduce a method to evaluate emotion competence objectively, which involves the analyses of frequency fluctuations of EEG signals and frontal EEG asymmetry. Then, we take an example of event-related potentials (ERP) study about the face recognition task and the discrimination of sad/happy/neutral emotional facial expressions task. Finally, we indicate the present difficulties in this research area, and advance the possible solution to resolve these problems.
{"title":"Recognition and analyses of EEG & ERP signals related to emotion: from the perspective of psychology","authors":"Yang Yuankui, Z. Jianzhong","doi":"10.1109/ICNIC.2005.1499851","DOIUrl":"https://doi.org/10.1109/ICNIC.2005.1499851","url":null,"abstract":"Electroencephalography (EEG) is widely used to record activities of human brain in the area of psychology for many years. With the development of technology, neural basis of functional areas of emotion processing is revealed gradually. In order to extract the useful information of emotion from the background of EEG signals and noise, we propose to combine methods of psychology and the technology of signal processing such as pattern recognition, etc. In this paper, we first review the psychological methods and signal processing technology in the field of emotion research, and point out the junctions of these two approaches. Secondly, we introduce a method to evaluate emotion competence objectively, which involves the analyses of frequency fluctuations of EEG signals and frontal EEG asymmetry. Then, we take an example of event-related potentials (ERP) study about the face recognition task and the discrimination of sad/happy/neutral emotional facial expressions task. Finally, we indicate the present difficulties in this research area, and advance the possible solution to resolve these problems.","PeriodicalId":169717,"journal":{"name":"Proceedings. 2005 First International Conference on Neural Interface and Control, 2005.","volume":"108 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131552548","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2005-05-26DOI: 10.1109/ICNIC.2005.1499845
X. Luo, C. Peng, X.M. Guo
In this paper, we use four basic morphological operators to construct a bandpass filter, and also investigate the construct method of the filter in detail. Furthermore, we give the algorithm flowchart of this filter. The result of experiment shows that this morphological filter can be applied to eliminate noise from EEG signal by two different length structure elements and it has advanced property that can remove noise without damage signal useful information. Using this algorithm, we can filter noise and extract spiky transients in EEG effectively.
{"title":"Using morphological filters to extract spiky transients in EEG","authors":"X. Luo, C. Peng, X.M. Guo","doi":"10.1109/ICNIC.2005.1499845","DOIUrl":"https://doi.org/10.1109/ICNIC.2005.1499845","url":null,"abstract":"In this paper, we use four basic morphological operators to construct a bandpass filter, and also investigate the construct method of the filter in detail. Furthermore, we give the algorithm flowchart of this filter. The result of experiment shows that this morphological filter can be applied to eliminate noise from EEG signal by two different length structure elements and it has advanced property that can remove noise without damage signal useful information. Using this algorithm, we can filter noise and extract spiky transients in EEG effectively.","PeriodicalId":169717,"journal":{"name":"Proceedings. 2005 First International Conference on Neural Interface and Control, 2005.","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122981042","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2005-05-26DOI: 10.1109/ICNIC.2005.1499881
X. Tian, Z. Xiao
A nonlinear model between brainstem, cortex and thalamus circuits is established on neural population level on Matlab/Simulink. The electric activities in this brain circuits are simulated. The output of this model is the derivatives of postsynaptic potentials from thalamus, which are reflected in EEG in both normal and epileptic EEGs. The epileptic EEGs are simulated via model with a dysfunction between brainstem and cortex, then controlled to normal by adding a perturbation to the cortex or sensory. The amplitude and the correlation dimension of the simulated EEG are used as the index of the dynamic behavior of EEG.
{"title":"Simulation and control of epileptic EEG via a nonlinear model on Simulink","authors":"X. Tian, Z. Xiao","doi":"10.1109/ICNIC.2005.1499881","DOIUrl":"https://doi.org/10.1109/ICNIC.2005.1499881","url":null,"abstract":"A nonlinear model between brainstem, cortex and thalamus circuits is established on neural population level on Matlab/Simulink. The electric activities in this brain circuits are simulated. The output of this model is the derivatives of postsynaptic potentials from thalamus, which are reflected in EEG in both normal and epileptic EEGs. The epileptic EEGs are simulated via model with a dysfunction between brainstem and cortex, then controlled to normal by adding a perturbation to the cortex or sensory. The amplitude and the correlation dimension of the simulated EEG are used as the index of the dynamic behavior of EEG.","PeriodicalId":169717,"journal":{"name":"Proceedings. 2005 First International Conference on Neural Interface and Control, 2005.","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123362473","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2005-05-26DOI: 10.1109/ICNIC.2005.1499877
Xu Qi, He Jiping, Wang Yongji, Xu Tao, Huang Jian
In this paper, we review various electrodes with individual design, address the influences of essential stimulator parameters and internal disturbances on the recruitment characteristics, and describe the control strategies of functional electrical stimulation (FES) musculoskeletal systems. The promise of possible directions for further research on safe and effective FES systems are also discussed.
{"title":"A review of fundamental mechanisms and techniques in functional electrical stimulation","authors":"Xu Qi, He Jiping, Wang Yongji, Xu Tao, Huang Jian","doi":"10.1109/ICNIC.2005.1499877","DOIUrl":"https://doi.org/10.1109/ICNIC.2005.1499877","url":null,"abstract":"In this paper, we review various electrodes with individual design, address the influences of essential stimulator parameters and internal disturbances on the recruitment characteristics, and describe the control strategies of functional electrical stimulation (FES) musculoskeletal systems. The promise of possible directions for further research on safe and effective FES systems are also discussed.","PeriodicalId":169717,"journal":{"name":"Proceedings. 2005 First International Conference on Neural Interface and Control, 2005.","volume":"391 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116665292","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2005-05-26DOI: 10.1109/ICNIC.2005.1499828
Wu Zhong-cheng, Kang Le, Shen Fei, Fang Bin
As more attention on human beings, developing an effective communication interface connecting the human brain to computer becomes an active research area in recent years. Until now, no efficient device can record the entire procedure of intrinsic human behavior information, including acquiring, transmitting, processing and outputting. In this paper, we offer a system which consists of computer and F-tablet, the later can acquire the kinematics and kinetics information of human handwriting. Joined with human beings, a vision-brain-hand to computer (VBH-C) interaction system is presented. In this human-in-the-loop-testing system, human beings acquire image, voice or text from computer by eyes or ears then write them down. As a closed-loop feedback portion, the designed F-Tablet acquires strokes of pen-up and pen-down, velocity and acceleration of pen-tip, three dimension forces of pen-plate contacting point and shape of character etc. The core part of the system, named as F-Tablet, is introduced which is able to acquire the trajectory and three-axis forces directly and simultaneously of pen-tip. A simple test will be done to judge the movements and forces controlling ability of different ages with the help of the system. Comparing with other brain-computer interface (BCI), VBH-C interface can offer more information, especially as a closed-loop and information feedback, it is easier for human decision pattern identification.
{"title":"The closed-loop human-computer interface: active information acquisition for vision-brain-hand to computer (VBH-C) interaction based on force tablet","authors":"Wu Zhong-cheng, Kang Le, Shen Fei, Fang Bin","doi":"10.1109/ICNIC.2005.1499828","DOIUrl":"https://doi.org/10.1109/ICNIC.2005.1499828","url":null,"abstract":"As more attention on human beings, developing an effective communication interface connecting the human brain to computer becomes an active research area in recent years. Until now, no efficient device can record the entire procedure of intrinsic human behavior information, including acquiring, transmitting, processing and outputting. In this paper, we offer a system which consists of computer and F-tablet, the later can acquire the kinematics and kinetics information of human handwriting. Joined with human beings, a vision-brain-hand to computer (VBH-C) interaction system is presented. In this human-in-the-loop-testing system, human beings acquire image, voice or text from computer by eyes or ears then write them down. As a closed-loop feedback portion, the designed F-Tablet acquires strokes of pen-up and pen-down, velocity and acceleration of pen-tip, three dimension forces of pen-plate contacting point and shape of character etc. The core part of the system, named as F-Tablet, is introduced which is able to acquire the trajectory and three-axis forces directly and simultaneously of pen-tip. A simple test will be done to judge the movements and forces controlling ability of different ages with the help of the system. Comparing with other brain-computer interface (BCI), VBH-C interface can offer more information, especially as a closed-loop and information feedback, it is easier for human decision pattern identification.","PeriodicalId":169717,"journal":{"name":"Proceedings. 2005 First International Conference on Neural Interface and Control, 2005.","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122253575","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2005-05-26DOI: 10.1109/ICNIC.2005.1499856
Liu Hailong, Wang Jue, Z. Chong-xun
The unsupervised method of growing hierarchical self-organizing map (GHSOM) was used to perform mental tasks classification. The GHSOM is an adaptive artificial neural network model with hierarchical architecture that is able to detect the hierarchical structure of data. The results indicate that GHSOM provides more detailed clustering information than SOM, and gives visual information about the separability of mental tasks in an intuitive way. The average classification accuracy across 130 task pairs by using GHSOM was up to 96.7%.
{"title":"Mental tasks classification and their EEG structures analysis by using the growing hierarchical self-organizing map","authors":"Liu Hailong, Wang Jue, Z. Chong-xun","doi":"10.1109/ICNIC.2005.1499856","DOIUrl":"https://doi.org/10.1109/ICNIC.2005.1499856","url":null,"abstract":"The unsupervised method of growing hierarchical self-organizing map (GHSOM) was used to perform mental tasks classification. The GHSOM is an adaptive artificial neural network model with hierarchical architecture that is able to detect the hierarchical structure of data. The results indicate that GHSOM provides more detailed clustering information than SOM, and gives visual information about the separability of mental tasks in an intuitive way. The average classification accuracy across 130 task pairs by using GHSOM was up to 96.7%.","PeriodicalId":169717,"journal":{"name":"Proceedings. 2005 First International Conference on Neural Interface and Control, 2005.","volume":"136 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131857478","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2005-05-26DOI: 10.1109/ICNIC.2005.1499857
Wu Hongyi, Xia Yang, Lai Yongxiu, L. Yansu, Y. Dezhong
In order to obtain a sensitive parameter to discriminate the different stages of epilepsy, we studied pilocarpine-induced epileptic rat's ECoG and EHG by bispectrum analysis method based on the assumption that EEG is nonGaussian and nonlinear signal. In this paper, we proposed a model of EEG signals according to the parameter model stimulated by nonGaussian white noise to estimate the bispectrum of EEG. The results showed that the bispectrum analysis is sensitive to the epileptic and nonepileptic EEG. From these results, the quantified parameters presenting the features of epileptic EEG can be found, which could be new evidences to clinical monitoring and predicting of seizure.
{"title":"Study of epileptic rat's EEG using bispectrum analysis","authors":"Wu Hongyi, Xia Yang, Lai Yongxiu, L. Yansu, Y. Dezhong","doi":"10.1109/ICNIC.2005.1499857","DOIUrl":"https://doi.org/10.1109/ICNIC.2005.1499857","url":null,"abstract":"In order to obtain a sensitive parameter to discriminate the different stages of epilepsy, we studied pilocarpine-induced epileptic rat's ECoG and EHG by bispectrum analysis method based on the assumption that EEG is nonGaussian and nonlinear signal. In this paper, we proposed a model of EEG signals according to the parameter model stimulated by nonGaussian white noise to estimate the bispectrum of EEG. The results showed that the bispectrum analysis is sensitive to the epileptic and nonepileptic EEG. From these results, the quantified parameters presenting the features of epileptic EEG can be found, which could be new evidences to clinical monitoring and predicting of seizure.","PeriodicalId":169717,"journal":{"name":"Proceedings. 2005 First International Conference on Neural Interface and Control, 2005.","volume":"323 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132945823","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2005-05-26DOI: 10.1109/ICNIC.2005.1499858
Zhang Lianyi, Z. Chong-xun
To have a safe, noninvasive, reliable and economic anesthetic depth indicator, the change of the a rhythm of electroencephalogram (EEG) signal on autocorrelation property during general intravenous anesthesia is investigated based on the effects of general anesthetics on the a rhythm of EEG in prefrontal cortex area. To synthesize the effects of correlated behavior, the contamination of muscle artifact is not removed from the EEG data. The autocorrelation analysis shows: 1) The EEG signals in prefrontal cortex area on autocorrelation are sensitive to different anesthesia depths during general anesthesia. The difference of autocorrelation trace from awareness to anesthesia is obvious. The change of autocorrelation trace is consistent with the anesthesia process; 2) The changes of autocorrelation in FP1-Cz channel and FP2-Cz channel with time are almost synchronous during general anesthesia. This means that 1-channel- recordings from prefrontal cortex are sufficient to monitor depth of anesthesia; 3) The value of autocorrelation in anesthesia fluctuates within a small range and is small than 20. This means that the value of autocorrelation is stable in anesthesia; 4) The differences of the range that the value of autocorrelation fluctuates in anesthesia present individual differences in a way. Being calculation simple, single channel and the transition of autocorrelation trace from awareness to anesthesia obvious, this technique may be ease to use, low running cost and can be applied in real time. Autocorrelation may provide a new method to monitor depth of anesthesia in clinic.
{"title":"A new method to monitor depth of anesthesia based on the autocorrelation EEG signals","authors":"Zhang Lianyi, Z. Chong-xun","doi":"10.1109/ICNIC.2005.1499858","DOIUrl":"https://doi.org/10.1109/ICNIC.2005.1499858","url":null,"abstract":"To have a safe, noninvasive, reliable and economic anesthetic depth indicator, the change of the a rhythm of electroencephalogram (EEG) signal on autocorrelation property during general intravenous anesthesia is investigated based on the effects of general anesthetics on the a rhythm of EEG in prefrontal cortex area. To synthesize the effects of correlated behavior, the contamination of muscle artifact is not removed from the EEG data. The autocorrelation analysis shows: 1) The EEG signals in prefrontal cortex area on autocorrelation are sensitive to different anesthesia depths during general anesthesia. The difference of autocorrelation trace from awareness to anesthesia is obvious. The change of autocorrelation trace is consistent with the anesthesia process; 2) The changes of autocorrelation in FP1-Cz channel and FP2-Cz channel with time are almost synchronous during general anesthesia. This means that 1-channel- recordings from prefrontal cortex are sufficient to monitor depth of anesthesia; 3) The value of autocorrelation in anesthesia fluctuates within a small range and is small than 20. This means that the value of autocorrelation is stable in anesthesia; 4) The differences of the range that the value of autocorrelation fluctuates in anesthesia present individual differences in a way. Being calculation simple, single channel and the transition of autocorrelation trace from awareness to anesthesia obvious, this technique may be ease to use, low running cost and can be applied in real time. Autocorrelation may provide a new method to monitor depth of anesthesia in clinic.","PeriodicalId":169717,"journal":{"name":"Proceedings. 2005 First International Conference on Neural Interface and Control, 2005.","volume":"103 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132258103","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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