Fetal electrocardiosignal self-adaptive blind extraction method based on generalized eigenvalue maximization

Abstract

The invention provides a fetal electrocardiosignal self-adaptive blind extraction method based on generalized eigenvalue maximization. The method comprises the following steps: collecting and acquiring blended data including a maternal and fetal electrophysiological signal; based on the self-adaptive real-time algorithm, calculating the covariance matrix characteristic value and characteristic vector of different delayed autocorrelation matrixes within the set period range; selecting the characteristic vector corresponding to the maximum eigenvalue as the blind separation vector so as to extract a fetal electrocardiosignal. The fetal electrocardiosignal self-adaptive blind extraction method utilizes the second-order statistics property of the signal to minimize the noise-to-signal ratio. The second-order statistic method is simple in calculation and small in operation, can still realize effective calculation when the rank of the autocorrelation matrix of the observation vector is close to zero, and can expand to real-time on-line algorithm more conveniently to facilitate product development.

Description

technical field [0001] The invention relates to the field of biomedical engineering, in particular to an adaptive blind extraction method of fetal electrocardiogram signals based on the maximization of generalized eigenvalues. Background technique [0002] Fetal electrocardiogram is an important physiological index to reflect the status of the fetus in the uterus. The fetal electrocardiogram is used to monitor the health status of the perinatal fetus, and to conduct early diagnosis of fetal hypoxia, intrauterine distress, congenital heart disease and other diseases during pregnancy. Can reduce birth defects and reduce mortality in newborns. [0003] Obtaining fetal ECG by placing electrodes on the mother's abdomen is a non-invasive detection method that is easy to obtain and has no risk to the fetus and pregnant women. The fetal ECG signal is a very weak physiological signal. The signal-to-noise ratio of the fetal ECG obtained from the abdomen is very low, and it is mixed w...

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Problems solved by technology

[0003] Obtaining fetal ECG by placing electrodes on the mother's abdomen is a non-invasive detection method that is easy to obtain and has no risk to the fetus and pregnant women. The fetal ECG signal is a very weak physiological signal. The signal-to-noise ratio of the fetal ECG obtained from the abdomen is very low, and it is mixed with a large number of noise signals, including the maternal ECG signal, power frequency interference, and myoelectricity. Signal, electrode interference, baseline drift, etc., especially the strength of the maternal ECG signal is 5-20 times that of the fetal ECG signal, and the fetal ECG signal is almost drowned by noise

Since the frequency of the fetal ECG signal overlaps with that of the mother's ECG signal and other noise signals, it is difficult to obtain a complete fetal ECG signal using ordinary filtering techniques.

[0004] Among the bioelectrical signals extracted from the mother's abdomen, the mother's ECG signal is the main strong interference signal. Therefore, it was first proposed to use adaptive filtering to separate the fetal ECG signal, and the mother's ECG signal was used as a reference signal. Since it is difficult to obtain a noise-free maternal ECG reference signal, power frequency, myoelectricity and other interference noise cannot be effectively suppressed or filtered out, so the adaptive filtering method has great limitations, and the effect in actual use is very poor

In recent years, the independent component analysis method used to separate fetal ECG signals has received extensive research and attention. The independent component analysis method assumes that each source signal is statistically independent, and requires that the observation data channel is equal to the number of source signals, which is difficult to guarantee in practice. , thus resulting in an unstable separation effect in practical applications

Secondly, the results of each independent component separated by the independent component analysis method are uncertain, and professionals need to judge which component is the fetal ECG signal by observing the results of each separated component, which greatly limits the real-time application of this method in practice.

Fetal ECG extraction is ultimately to achieve real-time fetal ECG monitoring, so the current extraction methods are immature both in theory and in existing technologies

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