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 in...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, ex-tremely fast calculation for very short data and anti-noise characteristic. For the well-known chaotic dynamical sys-tem―logistic map, it is shown that our complexity be-haves 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.展开更多
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...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 electro- cardiogram (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.展开更多
Multifractal characteristics of 16-channel hu-man electroencephalogram (EEG) signals under eye-closed rest are analyzed for the first time. The result shows that the EEGs from the different sites on the scalp have dif...Multifractal characteristics of 16-channel hu-man electroencephalogram (EEG) signals under eye-closed rest are analyzed for the first time. The result shows that the EEGs from the different sites on the scalp have different multifractal characteristics and the multifractal strength value a exhibits a kind of interleaving and left-right oppo-site distribution on scalp. This distribution rule is consistent with the localization of function and the lateralization theory in physiology. So Da can become an effective parameter to describe the brain potential character. And such a a stable distribution rule on sites of the scalp means a classic cerebral cortex active state.展开更多
Ventricular fibrillation (VF) caused by myo-cardial ischemia is one of the leading factors of death attrib-uted to cardiovascular diseases. It is particularly significantto predict VF and gain valuable time for clinic...Ventricular fibrillation (VF) caused by myo-cardial ischemia is one of the leading factors of death attrib-uted to cardiovascular diseases. It is particularly significantto predict VF and gain valuable time for clinic therapy. Five dogs are taken as the research objects and a VF model is introduced. The nonlinear characteristics of the ECGs before and after VF are investigated with nonlinear multi-parame-ter analysis methods, Gaussian kernel (GK) correlation es-timation algorithm and Lyapunov exponent estimation algo-rithm. Correlation entropy h2 is also presented. The results indicate that there are three parameters which will change at the same time with the conditions of myocardial ischemia,and any changes of a single parameter may be caused byother factors and mislead the judgment. Multi-parameter analysis is more reliable to reveal the heart conditions, and to predict VF without misjudgments.展开更多
文摘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, ex-tremely fast calculation for very short data and anti-noise characteristic. For the well-known chaotic dynamical sys-tem―logistic map, it is shown that our complexity be-haves 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.
文摘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 electro- cardiogram (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.
基金partly supported by the National Natural Science Foundation of China(Grant No.59905011)partly by the Science Foundation of Jiangsu Province(Grant No.2001XCYTSJB111)
文摘Multifractal characteristics of 16-channel hu-man electroencephalogram (EEG) signals under eye-closed rest are analyzed for the first time. The result shows that the EEGs from the different sites on the scalp have different multifractal characteristics and the multifractal strength value a exhibits a kind of interleaving and left-right oppo-site distribution on scalp. This distribution rule is consistent with the localization of function and the lateralization theory in physiology. So Da can become an effective parameter to describe the brain potential character. And such a a stable distribution rule on sites of the scalp means a classic cerebral cortex active state.
文摘Ventricular fibrillation (VF) caused by myo-cardial ischemia is one of the leading factors of death attrib-uted to cardiovascular diseases. It is particularly significantto predict VF and gain valuable time for clinic therapy. Five dogs are taken as the research objects and a VF model is introduced. The nonlinear characteristics of the ECGs before and after VF are investigated with nonlinear multi-parame-ter analysis methods, Gaussian kernel (GK) correlation es-timation algorithm and Lyapunov exponent estimation algo-rithm. Correlation entropy h2 is also presented. The results indicate that there are three parameters which will change at the same time with the conditions of myocardial ischemia,and any changes of a single parameter may be caused byother factors and mislead the judgment. Multi-parameter analysis is more reliable to reveal the heart conditions, and to predict VF without misjudgments.
