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Search Results: 1 - 10 of 7727 matches for " XinBao Ning "
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Nonlinearity degree of short-term heart rate variability signal
Chunhua Bian,Xinbao Ning
Chinese Science Bulletin , 2004, DOI: 10.1007/BF02900977
Abstract: A nonlinear autoregressive (NAR) model is built to model the heartbeat interval time series and the optimum model degree is proposed to be taken to evaluate the nonlinearity degree of heart rate variability (HRV). A group of healthy persons are studied and the results indicate that this method can effectively get nonlinear information from short (6–7 min) heartbeat series and consequently reflect the degree of heart rate variability, which supplies convenience in clinical application. Finally, a comparison with the traditional time domain method shows that the NAR model method can reflect the complexity of the whole signal and lessen the influence of noise and instability in the signal.
The base-scale entropy analysis of short-term heart rate variability signal
Jin Li,Xinbao Ning
Chinese Science Bulletin , 2005, DOI: 10.1360/982005-94
Abstract: The complexity of heart rate variability (HRV) signal can reflect physiological functions and healthy status of heart system. Detecting complexity of the short-term HRV signal has an important practical meaning. We introduce the base-scale entropy method to analyze the complexity of time series. The advantages of our method are its simplicity, extremely fast calculation for very short data and anti-noise characteristic. For the well-known chaotic dynamical system—logistic map, it is shown that our complexity behaves similarly to Lyapunov exponents, and is especially effective in the presence of random Gaussian noise. This paper addresses the use of base-scale entropy method to 3 low-dimensional nonlinear deterministic systems. At last, we apply this idea to short-term HRV signal, and the result shows the method could robustly identify patterns generated from healthy and pathologic states, as well as aging. The base-scale entropy can provide convenience in practically applications.
Multiscale analysis of heart beat interval increment series and its clinical significance
XiaoLin Huang,XinBao Ning,XinLong Wang
Chinese Science Bulletin , 2009, DOI: 10.1007/s11434-009-0596-2
Abstract: Analysis of multiscale entropy (MSE) and multiscale standard deviation (MSD) are performed for both the heart rate interval series and the interval increment series. For the interval series, it is found that, it is impractical to discriminate the diseases of atrial fibrillation (AF) and congestive heart failure (CHF) unambiguously from the healthy. A clear discrimination from the healthy, both young and old, however, can be made in the MSE analysis of the increment series where we find that both CHF and AF sufferers have significantly low MSE values in the whole range of time scales investigated, which reveals that there are common dynamic characteristics underlying these two different diseases. In addition, we propose the sample entropy (SE) corresponding to time scale factor 4 of increment series as a diagnosis index of both AF and CHF, and the reference threshold is recommended. Further indication that this index can help discriminate sensitively the mild heart failure (cardiac function classes 1 and 2) from the healthy gives a clue to early clinic diagnosis of CHF.
Effect of quercetin on chronic enhancement of spatial learning and memory of mice
Jiancai Liu,Huqing Yu,Xinbao Ning
Science China Life Sciences , 2006, DOI: 10.1007/s11427-006-2037-7
Abstract: In this study we evaluated the effect of quercetin on D-galactose-induced aged mice using the Morris water maze (MWM) test. Based on the free radical theory of aging, experiments were performed to study the possible biochemical mechanisms of glutathione (GSH) level and hydroxyl radical (OH ) in the hippocampus and cerebral cortex and the brain tissue enzyme activity of the mice. The results indicated that quercetin can enhance the exploratory behavior, spatial learning and memory of the mice. The effects relate with enhancing the brain functions and inhibiting oxidative stress by quercetin, and relate with increasing the GSH level and decreasing the OH content. These findings suggest that quercetin can work as a possible natural anti-aging pharmaceutical product.
Effect of quercetin on chronic enhancement of spatial learning and memory of mice
LIU Jiancai,YU Huqing &,NING Xinbao,

中国科学C辑(英文版) , 2006,
Abstract: In this study we evaluated the effect of quercetin on D-galactose-induced aged mice using the Morris water maze (MWM) test. Based on the free radical theory of aging,experiments were performed to study the possible biochemical mechanisms of glutathione (GSH) level and hydroxyl radical (OH-) in the hippocampus and cerebral cortex and the brain tissue enzyme activity of the mice. The results indicated that quercetin can enhance the exploratory behavior,spatial learning and memory of the mice. The effects relate with enhancing the brain functions and inhibiting oxidative stress by quercetin,and relate with increasing the GSH level and decreasing the OH-content. These findings suggest that quercetin can work as a possible natural anti-aging pharmaceutical product.
Nonlinearity degree of short-term heart rate variability signal
BIAN Chunhua,NING Xinbao,
BIANChunhua
,NINGXinbao

科学通报(英文版) , 2004,
Abstract: A nonlinear autoregressive (NAR) model is built to model the heartbeat interval time series and the optimum model degree is proposed to be taken to evaluate the nonlinearity degree of heart rate variability (HRV). A group of healthy persons are studied and the results indicate that this method can effectively get nonlinear information from short (6-7 min) heartbeat series and consequently reflect the degree of heart rate variability, which supplies convenience in clinical application. Finally, a comparison with the traditional time domain method shows that the NAR model method can reflect the complexity of the whole signal and lessen the influence of noise and instability in the signal.
Multifractal mass exponent spectrum of complex physiological time series
XiaoDong Yang,AiJun He,Yong Zhou,XinBao Ning
Chinese Science Bulletin , 2010, DOI: 10.1007/s11434-010-3276-3
Abstract: Physiological signal belongs to the kind of nonstationary and time-variant ones. Thus, the nonlinear analysis methods may be better to disclose its characteristics and mechanisms. There have been plenty of evidences that physiological signal generated by complex self-regulated system may have a fractal structure. In this work, we introduce a new measure to characterize multifractality, the mass exponent spectrum curvature, which can disclose the complexity of fractal structure from total bending degree of the spectrum. This parameter represents the nonlinear superpositions of the discrepancies of fractal dimension from all adjacent points in the curve and therefore solves the problem of original parameters for not fully reflecting the information of entire subsets in the fractal structure. The evaluations of deterministic fractal system Cantor measure validate that it is completely effective in exploring the complexity of chaotic series, and is also not affected by nonstability of the signal as well as disturbances of the noises. We then apply it to the analysis of human heart rate variability (HRV) signals and sleep electroencephalogram (EEG) signals. The experimental results show that this method can be better to discriminate cohorts under different physiological and pathological conditions. Compared with the indicator of singularity spectrum width, there are some improvements both on the computing efficiency and accuracy. Such conclusion may provide some valuable information for clinical diagnoses.
Mode entropy and dynamical analysis of irregularity for HFECG
Yinlin Xu,Xinbao Ning,Ying Chen,Jun Wang
Chinese Science Bulletin , 2004, DOI: 10.1007/BF03183418
Abstract: A new algorithm—ModEn (mode entropy) is proposed by analyzing and modifying ApEn (approximate entropy), so that the irregular analysis can be applied to the time series of short-term signals with broad amplitude and slow fluctuation (SBS signals); and the ModEn is introduced in the irregular dynamic analysis of high frequency electrocardiogram (HFECG) on a myocardium infarction (MI) animal model. It is shown that the ModEn has a considerable dynamic change in MI. Hence there are potential application values of the algorithm in the early stage diagnosis of heart disease.
A new measure to characterize multifractality of sleep electroencephalogram
Qianli Ma,Xinbao Ning,Jun Wang,Chunhua Bian
Chinese Science Bulletin , 2006, DOI: 10.1007/s11434-006-2213-y
Abstract: Traditional methods for nonlinear dynamic analysis, such as correlation dimension, Lyapunov exponent, approximate entropy, detrended fluctuation analysis, using a single parameter, cannot fully describe the extremely sophisticated behavior of electroencephalogram (EEG). The multifractal formalism reveals more “hidden” information of EEG by using singularity spectrum to characterize its nonlinear dynamics. In this paper, the zero-crossing time intervals of sleep EEG were studied using multifractal analysis. A new multifractal measure Δasα was proposed to describe the asymmetry of singularity spectrum, and compared with the singularity strength range Δα that was normally used as a degree indicator of multifractality. One-way analysis of variance and multiple comparison tests showed that the new measure we proposed gave better discrimination of sleep stages, especially in the discrimination between sleep and awake, and between sleep stages 3 and 4.
Complexity and characteristic frequency studies in ECG signals of mice based on multiple scale factors
XiaoDong Yang,AiJun He,Peng Liu,TongFeng Sun,XinBao Ning
Science China Life Sciences , 2011, DOI: 10.1007/s11427-011-4173-y
Abstract: Existing methods of physiological signal analysis based on nonlinear dynamic theories only examine the complexity difference of the signals under a single sampling frequency. We developed a technique to measure the multifractal characteristic parameter intimately associated with physiological activities through a frequency scale factor. This parameter is highly sensitive to physiological and pathological status. Mice received various drugs to imitate different physiological and pathological conditions, and the distributions of mass exponent spectrum curvature with scale factors from the electrocardiogram (ECG) signals of healthy and drug injected mice were determined. Next, we determined the characteristic frequency scope in which the signal was of the highest complexity and most sensitive to impaired cardiac function, and examined the relationships between heart rate, heartbeat dynamic complexity, and sensitive frequency scope of the ECG signal. We found that all animals exhibited a scale factor range in which the absolute magnitudes of ECG mass exponent spectrum curvature achieve the maximum, and this range (or frequency scope) is not changed with calculated data points or maximal coarse-grained scale factor. Further, the heart rate of mice was not necessarily associated with the nonlinear complexity of cardiac dynamics, but closely related to the most sensitive ECG frequency scope determined by characterization of this complex dynamic features for certain heartbeat conditions. Finally, we found that the health status of the hearts of mice was directly related to the heartbeat dynamic complexity, both of which were positively correlated within the scale factor around the extremum region of the multifractal parameter. With increasing heart rate, the sensitive frequency scope increased to a relatively high location. In conclusion, these data provide important theoretical and practical data for the early diagnosis of cardiac disorders.
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