Singularity spectra analysis of the ST segments of 12-lead electrocardiogram / 生物医学工程学杂志

By analysing the f(a) singularity spectra of the ST segments of the synchronous 12-lead ECG, we have found that the singularity spectrum is close to monofractality and its area is only half the area of the synchronous 12-lead ECG f(alpha) singularity spectrum. The ST segments of the synchronous 12-lead ECG signal also has f(alpha) singularity spectra distribution and it also has a reasonable varying scope. We have also found that the lead number of the ST segment f (alpha) singularity spectra for adults having coronary heart disease overstep the reasonable scope tends to increase over that of the ECG f(alpha) singularity spectra. These findings show that using the ST segments f(alpha) singularity spectra distribution of the synchronous 12-lead ECG is more effective than using the synchronous 12-lead ECG on the clinical analysis.

Multiscale entropy analysis of electrocardiogram / 生物医学工程学杂志

Using the algorithm proposed by Costa M, et al., we studied the multiscale entropy (MSE) of electrocardiogram. The sample entropy (SampEn) of the healthy subjects was found to be higher than that of the subjects with coronary heart disease or myocardial infarction. The healthy subjects' complexity was found to be the highest. The SampEn of the subjects with coronary heart disease was noted to be only slightly higher than that of the subjects with myocardial infarction. These findings show that the complexity of the subjects with coronary heart disease or myocardial infarction is distinctly lower than the complexity of the healthy ones, and the subjects suffereing from coronary heart disease are liable to the onset of myocardial infarction.

Influence of heart and brain disease on multifractal singularity spectrum of synchronous 12-lead ECG signals / 生物医学工程学杂志

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.

Research on the application of neural network to diagnosis of cardiopathy / 生物医学工程学杂志

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.