Research Of FECG Extraction And Heart Rate Variability Analysis

To enhance quality of borned child,lower the death rate of pregnant woman and fetal is an important mission of maternal and child health care.An effective fetal monitoring is a reliable ensurence for the safety of the mother and fetal during pregnancy.Fetal Electrocardiogram(FECG)is one of the most effective tools for early cardiac disease diagnosis of fetal and also it provides important information about the electrical activity of the fetal heart.The information of Fetal Heart Rate Variability(FHRV)can be obtained by calculating the RR intervals,which provides a quantitative tool for evaluating the synergetic control activity performed by the sympathetic and parasympathetic branches as well as reliable indications on fetal status.FECG can be recorded non-invasively from the abdomen of a pregnant woman in the clinical.However,the FECG is often interfered by noise,such as Maternal Electrocardiogram(MECG),Electromyographic(EMG)and so on.Therefore,how to extract the weak FECG effectively is one of the problems to be solved.This paper mainly analyzes the FECG extraction methods which based on the multi-lead/single-lead and then studies the spectrum estimates of FHRV.A strong robustness and fast convergence speed algorithm of the FECG extraction is proposed,and then establishing a measuring method of FHRV analysis in noninvasive so that fetal health and its development of the autonomic nervous system can be exactly evaluated.Firstly,the paper proposes a Fast Independent Component Analysis(Fast ICA)algorithm based on Modified BFGS(MBFGS)which can be used to extract FECG.Then for single-lead FECG extraction the paper proposes a new abdomenal ECG(AECG)dynamical model,and then the parallel Marginalized Particle Filter(par-MPF)is proposed for extracting FECG.Lastly,FHRV is analyzed based on Hilbert-Huang Transform(HHT).The main works of the paper are listed as fellow:1.The algorithm of the multi-lead FECG extraction is proposed based on chaos optimization algorithm and MBFGS.Firstly,research the theory of Independent Component Analysis(ICA)and Fast ICA.Secondly,the chaos optimization algorithm and MBFGS are combined to obtain a improved algorithm,which can solve the shortcoming of Fast ICA.Finally,the experiments are conducted by the synthetic signals and clinical signals respectively.The results indicate that the proposed method in this paper could well extract FECG.2.The algorithm of the single-lead FECG extraction is proposed based on ECG dynamical model and par-MPF.Firstly,a modified abdominal ECG dynamical model is proposed,in which both MECG and FECG are modelled.Secondly,a par-MPF is used for tracking the abdominal ECG,FECG and MECG are separated at the same time.Finally,several experiments are conducted by the synthetic signals and clinical signals respectively.The results indicate that the proposed method could well extract FECG and also it has a better robustness and a good stability.3.The algorithm of FHRV analysis is proposed based on HHT.Firstly,the Fetal Heart Rate(FHR)signals are obtained by detecting R peaks of FECG.Then the HHT is proposed to estimate the spectrum of FHRV thus a measuring method of FHRV analysis in the frequency domain is established.The proposed algorithms which effectively extract FECG combined with the quantitative analysis of FHRV will help obstetricians find abnormal development of fetus early and prevent fetus bad prognosis,reduce the morbidity and mortality of fetus.Therefore,it is of great significance to improve the eugenics level.