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| 1 | RESEARCH PROGRESS IN NONLINEAR ANALYSIS OF HEART ELECTRIC ACTIVITIES显示文摘Nonlinear science research is a hot point in the world. It has deepened our cognition of determinism and randomicity, simplicity and com-plexity, noise and order and it will profoundly influ-ence the progress of the study of natural science, including life science. Life is the most complex nonlinear system and heart is the core of lifecycle system. In the late more than 20 years, nonlinear research on heart electric activities has made much headway. The commonly used parameters are based on chaos and fractal theory, such as correlation dimension, Lyapunov ex-ponent, Kolmogorov entropy and multifractal singu-larity spectrum. This paper summarizes the commonly used methods in the nonlinear study of heart electric signal. Then, considering the shortages of the above tradi-tional nonlinear parameters, we mainly introduce the results on short-term heart rate variability (HRV) signal (500 R-R intervals) and HFECG signal (1-2s). Finally, we point out it is worthwhile to put emphasis on the study of the sensitive nonlinearity parameters of short-term heart electric signal and their dynamic character and clinical effectivity. | NING Xinbao BIAN Chunhua WANG Jun CHEN Ying | 2006 | Chinese Science Bulletin2006，51，4： | 16 |
| 2 | Distribution of correlation dimensions of synchronous 12-lead ECG signals显示文摘Correlation dimensions D2 of the synchronous 12-lead ECG signals have been investigated for the first time by distributed multi-sensor (multi-electrode) technique. The results show that correlation dimension of heart has the distributed characteristics. D2 calculated from different lead ECG signals is not a constant regardless of a healthy person or a coronary heart disease (CHD) patient with sinus rhythm. But with the same lead signal, D2 of CHD patients is evidently smaller than that of a healthy person except I, II, III leads. A healthy person and CHD patient can be identified by D2 statistically and D2 shows the potential application in the diagnosis of the CHD patients. | WANG Zhenzhou NING Xinbao ZHANG Yu DU Gonghuan | 2000 | Chinese Science Bulletin2000，45，17： | 13 |
| 3 | Multifractal mass exponent spectrum of complex physiological time series显示文摘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. | YANG XiaoDong HE AiJun ZHOU Yong NING XinBao | 2010 | Chinese Science Bulletin2010，55，19： | 7 |
| 4 | Lyapunov exponents for synchronous 12-lead ECG signals显示文摘The Lyapunov exponents of synchronous 12-lead ECG signals have been investigated for the first time using a multi-sensor (electrode) technique. The results show that the Lyapunov exponents computed from different locations on the body surface are not the same, but have a distribution characteristic for the ECG signals recorded from coronary artery disease (CAD) patients with sinus rhythms and for signals from healthy older people. The maximum Lyapunov exponent L1 of all signals is positive. While all the others are negative, so the ECG signal has chaotic characteristics. With the same leads, L1 of CAD patients is less than that of healthy people, so the CAD patients and healthy people can be classified by L1, L1 therefore has potential values in the diagnosis of heart disease. | WANG Zhenzhou LI Zheng WEI Yixiang NING Xinbao LIN Yuzheng | 2002 | Chinese Science Bulletin2002，47，21： | 7 |
| 5 | A new measure to characterize multifractality of sleep electroencephalogram显示文摘Traditional methods for nonlinear dy-namic 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 for-malism reveals more “hidden” information of EEG by using singularity spectrum to characterize its nonlin-ear dynamics. In this paper,the zero-crossing time intervals of sleep EEG were studied using multifractal analysis. A new multifractal measure Δasα was pro-posed to describe the asymmetry of singularity spec-trum,and compared with the singularity strength range Δα that was normally used as a degree indi-cator 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 be-tween sleep and awake,and between sleep stages 3 and 4. | MA Qianli NING Xinbao WANG Jun BIAN Chunhua | 2006 | Chinese Science Bulletin2006，51，24： | 3 |
| 6 | Nonlinear short-term heart rate variability prediction of spontaneous ventricular tachyarrhythmia显示文摘As malign ventricular tachyarrhythmias triggering sudden cardiac death (SCD), both ventricular tachycardia (VT) and ventricular fibrillation (VF) are major causes of mortality. The most efficient ther- apy for SCD prevention is implantable cardioverter defibrillators (ICD). The ICD can accurately and ef- fectively identify the forthcoming of fatal ventricular tachyarrhythmias and deliver a shock in order to restore patients’ normal sinus rhythm. In this study, two nonlinear complexity measures based on en- tropy: approximate entropy (ApEn) and sample entropy (SampEn) as well as two time linear indices: the mean RR interval (the average of time intervals between consecutive R-waves) and the standard devia- tion of RR intervals were used for short-term forecasting of VT-VF occurrence. The last small sections of interbeat intervals preceding 135 VT-VF episodes from 78 patients stored by the ICD were analyzed and compared with individually acquired control time series (CON series) from the same patients, which are normally intrinsic sinus rhythms. The results demonstrate that in addition to an obvious in- crease in heart rates of the patients, the values of two entropy measures are significantly smaller for VT-VF episodes than those for CON series. Conclusions can be drawn that when a ventricular tach- yarrhythmia approaches, the sympathetic tone of the patients is increased, and the complexity of their RR intervals immediately before the onset of VT-VF events is obviously lower than that of RR intervals recorded during sinus rhythms. For a better separation, the optimal range of threshold r is determined for two algorithms. ApEn and SampEn measures might be the suitable nonlinear parameters for short- term prediction of life-threatening ventricular tachyarrhythmias in the application of the cardioversion and defibrillation. | ZHUANG JianJun NING XinBao DU SiDan WANG ZhenZhou HUO ChengYu YANG Xi FAN AiHua | 2008 | Chinese Science Bulletin2008，53，16： | 2 |
| 7 | Multiscale analysis of heart beat interval increment series and its clinical significance显示文摘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 diag-nosis 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. | HUANG XiaoLin NING XinBao WANG XinLong | 2009 | Chinese Science Bulletin2009，54，20： | 2 |
| 8 | Sign series entropy analysis of short-term heart rate variability显示文摘Complexity and nonlinearity approaches can be used to study the temporal and structural order in heart rate variability (HRV) signal, which is helpful for understanding the underlying rule and physiological essence of cardiovascular regulation. For clinical applications, methods suitable for short-term HRV analysis are more valuable. In this paper, sign series entropy analysis (SSEA) is proposed to characterize the feature of direction variation of HRV. The results show that SSEA method can detect sensitively physiological and pathological changes from short-term HRV signals, and the method also shows its robustness to nonstationarity and noise. Thus, it is suggested as an efficient way for the analysis of clinical HRV and other complex physiological signals. | BIAN ChunHua MA QianLi SI JunFeng WU XuHui SHAO Jun NING XinBao WANG DongJin | 2009 | Chinese Science Bulletin2009，54，24： | 2 |
| 9 | Multifractal analysis of resting state fMRI series in default mode network: age and gender effects显示文摘Age-related changes of resting state in default mode network(DMN)may provide new clues to the developing mechanism of normal brain as well as early diagnosis and therapy of some neuropsychiatric disorders.The application of multifractal theory to functional magnetic resonance imaging(fMRI)signals has recently raised increasing attention.We aim to explore the multifractal characteristics underlying the resting state functional magnetic resonance imaging(rs-fMRI)series extracted from DMN,and two issues are mainly discussed:(1)whether there exist multifractals in rs-fMRI series;(2)whether it is possible to distinguish between the different ages or genders by means of multifractal characteristics.Results demonstrated the existence of multifractals in rs-fMRI series in DMN.In addition,slight differences between young subjects and middle-aged or elderly subjects can be successfully detected by Dasa,a modified measure we proposed.Furthermore,it is revealed that the rs-fMRI series from young subjects possess smaller averaged scale index and weaker long range correlation,while those from middle-aged or elderly people present increasing averaged scale index andstronger long range correlation.Whereas no significant statistical differences has been found between male and female group.Our results,therefore,highlight the potential usefulness of multifractal analysis in fMRI series of a certain brain region,and provide important insights into healthy aging in DMN. | Huangjing Ni Xiaolin Huang Xinbao Ning Chengyu Huo Tiebing Liu De Ben | 2014 | Chinese Science Bulletin2014，59，25： | 2 |
| 10 | Dynamic complexity detection in shortterm physiological series using base-scale entropy显示文摘 | Li Jin Ning Xinbao | 2006 | Physical Review E2006，73，05： | 1 |
| 11 | Highdimensional time irreversibility analysis of human interbeatintervals显示文摘 | Hou Fengzhen Ning Xinbao Zhuang Jianjun | 2011 | Medical Engineering and Physics2011，33，5： | 1 |
| 12 | Modulation of heart disease information to the 12-lead ECG multifractal distribution显示文摘 | Wang Jan Ning Xinbao Chen Ying | 2003 | Physica A2003，325，34： | 1 |
| 13 | Multifractal analysis of electronic cardiogram taken from healthy and unhealthy adult subjects显示文摘 | Wang Jun Ning Xinbao Chen Ying | 2003 | Physica A2003，323，1： | 1 |
| 14 | Nonlinear dynamic characteristics analysis of synchronous 12-lead ECG signals显示文摘 | Wang Zhenzhou Ning Xinbao Zhang Yu | 2000 | IEEE Engineering in Medicine and Biology2000，19，5： | 1 |
| 15 | High-dimensional time irreversibility analysis of human interbeat intervals显示文摘 | Hou Fengzhen Ning Xinbao Zhuang Jianjun | 2011 | Med Eng Phys2011，33，： | 1 |
| 16 | MultifractM anMysis of electronic cardiogram taken from heMthy and unheMthy adult subjects显示文摘 | Wang Jun Ning Xinbao Chen Ying | 2003 | Physica A2003，323，： | 1 |
| 17 | Multiscale multifractality analysis of a 12-lead electrocardiogram显示文摘 | Wang Jun Ning Xinbao Ma Qianli | 2005 | Physical Review E2005，，06： | 1 |
| 18 | Dynamical complexity detection in short-term physiological series using base-scale entropy显示文摘 | Li Jin Ning Xinbao | 2006 | Physical Review E2006，，05： | 1 |
| 19 | Approximate entropy analysis of short-term HFECG based on wave mode显示文摘 | Ning Xinbao Xu Yinlin Wang Jun | 2005 | Physica A2005，，346： | 1 |
| 20 | Detection and identification of 12-lead synchronous EGG waveform显示文摘 | Ning Xinbao Li Dehua Ding Songwei | 2004 | Journal of Nanjing University:Natural Sciences2004，40，1： | 1 |
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