This is a research carried out to explore a pragmatic way of BCI based imaging movement, i. e. to extract the feature of EEG for reflecting different thinking by searching suitable methods of signal extraction and recognition algorithm processing, to boost the recognition rate of communication for BCI system, and finally to establish a substantial theory and experimental support for BCI application. In this paper, different mental tasks for imaging left-right hands movement from 6 subjects were studied in three different time sections (hint keying at 2s, 1s and 0s after appearance of arrow). Then we used wavelet analysis and Feed-forward Back-propagation Neural Network (BP-NN) method for processing and analyzing the experimental data of off-line. Delay time delta t2, delta t1 and delta t0 for all subjects in the three different time sections were analyzed. There was significant difference between delta to and delta t2 or delta t1 (P<0.05), but no significant difference was noted between delta t2 and delta t1 (P>0.05). The average results of recognition rate were 65%, 86.67% and 72%, respectively. There were obviously different features for imaging left-right hands movement about 0.5-1s before actual movement; these features displayed significant difference. We got higher recognition rate of communication under the hint keying at about 1s after the appearance of arrow. These showed the feasibility of using the feature signals extracted from the project as the external control signals for BCI system, and demon strated that the project provided new ideas and methods for feature extraction and classification of mental tasks for BCI.
Algorithms ; Brain ; physiology ; Electroencephalography ; methods ; Evoked Potentials, Motor ; physiology ; Hand ; physiology ; Humans ; Movement ; physiology ; Neural Networks (Computer) ; Pattern Recognition, Physiological ; Signal Processing, Computer-Assisted ; Thinking ; physiology ; User-Computer Interface

Objective: To investigate the characteristics, temporal trend of silicosis, and provide basis for risk assessment and precise prevention and control of occupational diseases. Methods: Using descriptive statistics to analyze the reported cases of silicosis by SPSS 20.0 software. Reported silicosis cases, the constituent ratio, the incidence age and the working age at onset were analyzed by a linear trend test. Analyzing the variation trends of regional, industry, economic type and enterprise scale distributions by the chi-square trend test. Moreover, using Moran's I method for spatial autocorrelation analysis and trend-surface analysis. Results: (1) During 2006 to 2015, Guangdong province had reported 1, 428 cases of silicosis, mainly gathered in Foshan, Zhongshan, Guangzhou, Shenzhen, which included 1391 male cases accounting for 97.41%. And the average incidence age was 45 (39, 51) . The average working age of onset was 9 (5.5, 15) . In economic type distribution, the private economy took the main part, accounting for 59.1%. In enterprise scale distribution, it was dominated by small and medium enterprises (SMEs) , accounting for 32.4% and 37.3% respectively. In industry distribution, most cases were gathered in materials and mining industry, accounting for 32.1% and 22.9% respectively. (2) The number of silicosis cases, the incidence age and the working age of onset showed a rising trend (P<0.01) . Meanwhile, the constituent ratios of medium-sized enterprises and building materials industry were increasing (P<0.05) . The annual variation trends of regional, economic type and age distributions were not statistically significant (P> 0.05) . (3) The spatial distribution trend showed an inverted U type, which was firstly raised and then declined from south to north and from east to west. The distribution characteristic demonstrated some high-high cluster areas, including Chancheng, Nanhai, Shunde, Panyu, Dongguan, Pengjiang, and Zhongshan. While Wuhua showed a high-low outlier form (P<0.01) . Conclusion Silicosis cases, age and working age of onset were on the rise, as well as the industry and enterprise scale distributions of occupational diseases presented a certain trend in Guangdong province from 2006 to 2015. There were high-high cluster and high-low outlier phenomena in spatial distribution with spatial correlation. Therefore, our work of silicosis epidemic trend and distribution may provide some bases for the occupational disease risk assessment and control.

OBJECTIVE: To explore the application of the autoregressive integrated moving average model( ARIMA model)in predicting incidence of occupational noise-induced deafness( ONID). METHODS: The ARIMA model was established and validated based on the number of new onset ONID cases in Guangdong Province from 2006 to 2015. Then the ARIMA model was used to predict the trend of new onset ONID cases from 2016 to 2020. RESULTS: The number of new ONID cases in Guangdong Province from 2006 to 2015 showed an exponential growth trend. The optimal model fitted with the number of new onset ONID cases from 2006 to 2015 was the ARIMA( 2,2,2) model,which better match the number of new onset ONID cases from 2008 to 2015. According to the ARIMA( 2,2,2) model,the number of new onset ONID cases in Guangdong Province will continue to have a rapidly increasing trend from 2016 to 2020. CONCLUSION: The ARIMA model based on time series matches the time trend of ONID onset,and it can be used for the prediction of ONID incidence trend.

OBJECTIVE: To analyze the epidemiological characteristics and predict epidemiological trends of occupational chemical poisoning,based on directly reported data during 2006-2015 in Guangdong Province. METHODS: The data of patients with occupational chemical poisoning reported from National Information Surveillance System for Occupational Disease and Occupational Health from 2006 to 2015 in Guangdong Province were collected. The epidemiological characteristics were retrospectively analyzed. The autoregressive integral moving average model( ARIMA model) was established and validated based on the number of the new onset cases and was used to predict the trends of occupational chemical poisoning from 2017 to 2020 in Guangdong Province. RESULTS: From 2006 to 2015,1 288 new cases of occupational chemical poisoning were reported in Guangdong Province,which accounted for 24. 4% of the total number of new cases of occupational diseases in the province( 5 283 cases). Among the new cases,the percentage of acute and chronic poisoning was 21. 7%( 279/1 288) and 78. 3%( 1 009/1 288). There was 74. 7%( 962/1 288) of organic solvent poisoning. Five kinds of new occupational chemical poisoning were found. Most of the new cases were male,accounting for 56. 7%( 729/1 288). They were mainly distributed and concentrated in Pearl River Delta Region,accounting for 95. 9%(1 235/1 288). Shenzhen,Dongguan and Guangzhou were the most three cities which had 425,325 and 209 cases respectively,all of them accounted for 74. 4%( 959/1 288). The new cases of poisoning mainly distributed in medium and small enterprises( 72. 0%),private economic enterprises( 50. 9%) and manufacturing industries(70. 5%). The number of occupational chemical poisoning diseases decreased first,and increased,and the proportion to the total number of occupational diseases in Guangdong Province showed a straight downward trend(P < 0. 01). The median age at diagnosis was 35 years old and the median work year at diagnosis was 2. 0 years,and both of them showed an increasing trend( P < 0. 01). CONCLUSION: Occupational chemical poisoning in Guangdong Province has certain characteristic of crowd aggregation and epidemic trends.