Biomedical subjects

Xinbao Ning

Publications and source records attributed to Xinbao Ning.

7 recordsLinked to original sources

PubMed2006

Dynamical complexity detection in short-term physiological series using base-scale entropy.

Physiological systems generate complex fluctuations in their output signals that reflect the underlying dynamics. The base-scale entropy method was proposed as a complexity measure to investigate the complexity of time series. The advantages of this method are simplicity and extremely fast calculation for very short data sets. This method enables analyzing very short, nonstationary, and noisy data sets. We employed this method for short-term physiological time series for analysis of heart-rate variability signals. The results show that the simple and easily calculated measure can effectively detect the complexity dissimilarity of physiological time series in different physiological or pathological states, which is convenient for clinical applications.

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PubMed2006

Multifractal ECG mapping of ventricular epicardium during regional ischemia in the pig.

Myocardial ischemia creates abnormal electrophysiological substrates that can result in life-threatening ventricular arrhythmias. Early clinical identification of ischemia in patients is important to managing their condition. We analyzed electrograms from an ischemia-reperfusion animal model in order to investigate the relationship between myocardial ischemia and variability of electrocardiogram (ECG) multifractality. Ventricular epicardial electropotential maps from the anesthetized pig during LAD ischemia-reperfusion were analyzed using multifractal methods. A new parameter called the singularity spectrum area reference dispersion (SARD) is presented to represent the temporal evolution of multifractality. By contrasting the ventricular epicardial SARD and range of singularity strength (delta alpha) maps against activation-recovery interval (ARI) maps, we found that the dispersions of SARD and dleta alpha increased following the onset of ischemia and decreased with tissue recovery. In addition, steep spatial gradients of SARD and delta alpha corresponded to locations of ischemia, although the distribution of multifractality did not reflect the degree of myocardial ischemia. However, the multifractality of the ventricular epicardial electrograms was useful for classifying the recoverability of ischemic tissue. Myocardial ischemia significantly influenced the multifractality of ventricular electrical activity. Recoverability of ischemic myocardium can be classified using the multifractality of ventricular epicardial electrograms. The location and size of regions of severe ischemic myocardium with poor recoverability is detectable using these methods.

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PubMed2005

Multiscale multifractality analysis of a 12-lead electrocardiogram.

This paper proposes that a multiscale multifractality (MSMF) method be adopted for the spatiotemporal analysis of 12-lead ECG. By using this method, the authors find that, in some frequency range, 12-lead ECG has a more complex fractal structure, and the position of the largest singularity strength range delta alpha is not relying on the data length but on the scale factor. By determining the inflexion, the MSMF proves to be more sensitive in displaying the trend that the singularity strength range delta alpha of human ECG decreases with human aging.

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PubMed2005

[Influence of heart and brain disease on multifractal singularity spectrum of synchronous 12-lead ECG signals].

We analyzed the multifractal singularity spectrum of synchronous 12-lead ECG (electrocardiogram) signals from heart and brain disease patients, and found that multifractal curves of different leads do not overlap each other. After calculating the scope of the singularity strength, we noticed that the averages of scope are not the same in different subjects,and the dispersing degree is also different in someone's different leads. Both the deltaalpha, the average of the deltaalpha, and the dispersing degree deltaalpha (be defined as standard deviation) of the deltaalpha of every one's 12-lead ECG were computed. Then, a comparison was made between the spectrum of the healthy subjects and the heart disease patients. The results showed that their deltaalpha are close, but their deltaalpha are markedly different. Also the healthy subjects and brain disease patients were compared, we found that their deltaalpha are close, but their deltaalpha are markedly different. These indicate that the character of multifractal spectrum is controlled by both the neurosystem of body and the self-syntonic property of cardiac structures. Furthermore, the deltaalpha is related with the neuroautonomic control of people's body on the ECG, and the deltaalpha is related with the anisotropy of the heterogeneous tissue and the electric signal propagation in heart.

Aged↗

PubMed2004

[Research on the application of neural network to diagnosis of cardiopathy].

Neural networks can fit any nonlinear function. After drawing out several characteristic parameters from the three-dimension spectrum for high frequency QRS waves, we input them into the network and trained the network. In this way, we can get a m-dimension curved surface in the m-dimension space which is constructed by those parameters, and this curved surface divides the space into two parts: the unhealthiness and the health. Now, the network can automatically distinguish between the healthiness and the unhealthiness according to their three-dimension spectrum for high frequency QRS waves.

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PubMed2004

[Dynamical analysis of the nonlinearity in the model of acute myocardial ischemia].

By analyzing the electrocardiosignals, many scholars have found remarkable and outstanding dynamic characteristics in both normal hearts and sick hearts. Based on those findings, a model of acute myocardial ischemia of six rabbits is designed by us and is presented here. The electrocardiogram (ECG) signals of different time series are calculated, and the figures of correlation dimensions-time and the maximum Lyapunov exponents-time are given. The results show that the existence of myocardial ischemia will bring the decline of the value of maximum Lyapunov exponents and correlation dimensions, after the figures being analyzed with electrophysiological and anatomical knowledge. The maximum Lyapunov exponents of ECG demonstrate the chaotic quality of the system and the correlation dimension of ECG demonstrates the complexity of the system, and there is no explicit relation between them. Correlation dimensions of ECG signals might be more influenced by partial heart system, compared with the maximum Lyapunov exponents of ECG signals.

Animals↗

PubMed2004

[A primary investigation on the dynamic changes of correlation dimension of animal's ECG signals].

The dynamic changes of synchronous 12-lead ECG signal's correlation dimension (D2) of an anesthetized rabbit were investigated primarily under three different pathologic conditions. The results showed that the D2 derived from different lead signals was not a constant whether the rabbit was in normal state or in emergent myocardial infarction condition, it demonstrated distribution characteristic. Compared with the same lead signal, D2 of limb lead almost kept constant, D2 of chest lead got higher when the sphere of emergent ischemia extended larger. D2 showed the potential application in the diagnosis of coronary heart disease.

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