In order to explore the correlation between the adjacent segments of a long term EEG, an improved principal component analysis(PCA) method based on mutual information algorithm is proposed. A one-dimension EEG time se...In order to explore the correlation between the adjacent segments of a long term EEG, an improved principal component analysis(PCA) method based on mutual information algorithm is proposed. A one-dimension EEG time series is divided equally into many segments, so that each segment can be regarded as an independent variables and multi-segmented EEG can be expressed as a data matrix. Then, we substitute mutual information matrix for covariance matrix in PCA and conduct the relevance analysis of segmented EEG. The experimental results show that the contribution rate of first principal component(FPC) of segmented EEG is more larger than others, which can effectively reflect the difference of epileptic EEG and normal EEG with the change of segment number. In addition, the evolution of FPC conduce to identify the time-segment locations of abnormal dynamic processes of brain activities,these conclusions are helpful for the clinical analysis of EEG.展开更多
A new segmented correlating decoder of synchronous optical CDMA using modified prime sequence codes is proposed. The performance of the proposed system is analyzed under the assumption of Poisson shot noise model for ...A new segmented correlating decoder of synchronous optical CDMA using modified prime sequence codes is proposed. The performance of the proposed system is analyzed under the assumption of Poisson shot noise model for the receiver photodetector. The decoder technique is shown to be more effective to improve the bit error probability performance than the method using an optical hard-limiter.展开更多
Objective:To investigate and thoroughly understand the physical examination results of retired employees from a certain unit in Beijing,analyze their bone mineral density(BMD),and identify risk factors that may indica...Objective:To investigate and thoroughly understand the physical examination results of retired employees from a certain unit in Beijing,analyze their bone mineral density(BMD),and identify risk factors that may indicate osteoporosis.This provides a reference for the individualized prevention,identification,and control of osteoporosis among retired employees.Methods:The bone mineral density and potential factors of 148 retired employees from a unit in 2023 were analyzed and categorized into osteoporosis and non-osteoporosis groups.Key factors from the physical examinations of the two groups were compared.Spearman’s correlation analysis was used to determine the correlation between key factors and osteoporosis.Significant key factors were included in a regression analysis.A multivariate binary logistics regression was employed to identify risk factors indicative of osteoporosis.Results:Correlation analysis revealed that gender,age,and ECG ST-segment length were significantly associated with osteoporosis.Regression analysis showed that for each additional year of age,the likelihood of developing osteoporosis increased by 1.058 times;females were 2.865 times more likely to develop osteoporosis compared to males;the longer the ECG ST-segment,the higher the likelihood of osteoporosis.Conclusion:Gender,age,and ECG ST-segment length are significantly associated with osteoporosis.These indicators can provide reference points for early identification,early intervention,and reducing the incidence of osteoporosis in clinical settings.展开更多
基金Natural Science Foundatoin of Fujian Province of Chinagrant number:2010J01210,2012J01280
文摘In order to explore the correlation between the adjacent segments of a long term EEG, an improved principal component analysis(PCA) method based on mutual information algorithm is proposed. A one-dimension EEG time series is divided equally into many segments, so that each segment can be regarded as an independent variables and multi-segmented EEG can be expressed as a data matrix. Then, we substitute mutual information matrix for covariance matrix in PCA and conduct the relevance analysis of segmented EEG. The experimental results show that the contribution rate of first principal component(FPC) of segmented EEG is more larger than others, which can effectively reflect the difference of epileptic EEG and normal EEG with the change of segment number. In addition, the evolution of FPC conduce to identify the time-segment locations of abnormal dynamic processes of brain activities,these conclusions are helpful for the clinical analysis of EEG.
文摘A new segmented correlating decoder of synchronous optical CDMA using modified prime sequence codes is proposed. The performance of the proposed system is analyzed under the assumption of Poisson shot noise model for the receiver photodetector. The decoder technique is shown to be more effective to improve the bit error probability performance than the method using an optical hard-limiter.
文摘Objective:To investigate and thoroughly understand the physical examination results of retired employees from a certain unit in Beijing,analyze their bone mineral density(BMD),and identify risk factors that may indicate osteoporosis.This provides a reference for the individualized prevention,identification,and control of osteoporosis among retired employees.Methods:The bone mineral density and potential factors of 148 retired employees from a unit in 2023 were analyzed and categorized into osteoporosis and non-osteoporosis groups.Key factors from the physical examinations of the two groups were compared.Spearman’s correlation analysis was used to determine the correlation between key factors and osteoporosis.Significant key factors were included in a regression analysis.A multivariate binary logistics regression was employed to identify risk factors indicative of osteoporosis.Results:Correlation analysis revealed that gender,age,and ECG ST-segment length were significantly associated with osteoporosis.Regression analysis showed that for each additional year of age,the likelihood of developing osteoporosis increased by 1.058 times;females were 2.865 times more likely to develop osteoporosis compared to males;the longer the ECG ST-segment,the higher the likelihood of osteoporosis.Conclusion:Gender,age,and ECG ST-segment length are significantly associated with osteoporosis.These indicators can provide reference points for early identification,early intervention,and reducing the incidence of osteoporosis in clinical settings.
