Research On Classification Method For Ventricular Fibrillation And Ventricular Tachycardia Based On The Lempel-Ziv Complexity And Signal Decomposition

In recent years, the incidence of cardiovascular disease is increasing. In the study of cardiovascular disease, it was found that the function of the heart of the recession and functional lesions that caused by heart disease was account for a large proportion. Sudden cardiac death is the most serious arrhythmia symptoms and manifestations, if not timely defibrillation to patient, sudden cardiac death means the end of life, and as such, many countries of the medical and health sector and biomedical research centers are positive to carry out the research. After several years of research and testing, it was showed that vast majority of cases of sudden cardiac death was due to ventricular fibrillation(VF) or sustained ventricular tachycardia(VT). Moreover, treatment measures taken by the two diseases are different. Patients with VF, we must to be defibrillation; and for patients with VT, it will have to be low-energy complex heart rate. If VT was wrongly accused of VF, or VF was wrongly accused of VT, the result was fatal. Accordingly, we proposed an efficient algorithm to automatically detect, which can help reduce the workload of medical staff, and its clinical application in promoting the contribution will be very great.From the study of the current number of heart telecommunications chart(ECG), it can be classified as Category nonlinear dynamics. It has an obvious advantages for using nonlinear dynamics method to VF and VT detection. Because the frequency of ventricular fibrillation is 200-500 bpm, while the frequency of ventricular tachycardia is about 150-200 bpm, baseline drift and noise frequency interference frequencies are below 50 Hz, we would take into account the signal decomposition method, which the ECG was decomposed into a series of sub-band signals, and these sub-band signals contains important information of the original signal. A new algorithm uses the complexity and the time series decomposition was protected. These methods have significantly improved overall performance in terms of accuracy and speed and considerable practical value. Furthermore, it is develop a new way to joint using a variety of parameters to detect VF and VTIn addition, the algorithm of the LZ complexity has been improved, which it can be applied for VF and VT detection. If the value of binary numbers L is very small, then it is most likely not be fully manifested the dynamic characteristics of the sequence itself; if L is very large, the original sequence is decomposed into small intervals, these values that obtained the difference is not significant. In contrast, the computation time of the LZ complexity is increases and the running time is grows, although this method retains many details of the original series, provide accurate and timely treatment is very important for patients that suffering sudden cardiac death. Therefore, this method is not appropriate. To solve this problem, the article refers to the complexity of the index f, six samples of VT and six samples of VF is used in this article, the experimentally determined hexadecimal L(L = 60). Introducing complexity index f, the performance of LZ complexity has been greatly improved.Heart disease is becoming a major threat to human health, its pathogenesis is complex, the most important point is that the application of nonlinear dynamics. This proposed method also needs to be applied in practice, only way can achieve its life-saving value.