Fetal heart rate extraction method based on maternal electrocardiosignals

Abstract

The invention discloses a fetal heart rate extraction method based on maternal electrocardiosignals. The method includes the steps that maternal abdominal wall mixed signals serve as input signals, the maternal abdominal wall mixed signals are preprocessed through low-pass filtering and moving average filtering, a channel of maternal abdominal wall mixed signals with the best electrocardiosignal quality are selected through a signal quality estimation method to serve as to-be-processed signals, the energy of the signals at every moment within the 20-40 Hz frequency band is calculated through Mexican hat wavelet transformation, maternal QRS waves are recognized from an energy-time series and removed, and a peak corresponding to the remaining part of the energy-time series is the fetal electrocardiogram. The whole method is simple and convenient and easy to implement, fetal electrocardiosignals can be effectively extracted from the maternal abdominal wall mixed electrocardiosignals, and a guarantee is provided for a doctor in diagnosis and treatment of fetal diseases.

Description

technical field [0001] The invention belongs to the technical field of medical devices, and in particular relates to a fetal heart rate extraction method based on maternal electrocardiogram signals. Background technique [0002] Fetal ECG signal is an important and common one among various ECG signals. At present, the fetal development in the womb is mainly diagnosed clinically by monitoring the changes of heart sound, heartbeat and electrocardiogram. Among them, the fetal electrocardiogram can best reflect the fetal heart activity, is more sensitive to problems in the fetal development process, and can provide a more reliable basis for clinical diagnosis. However, the fetal ECG signal is very weak, and the extraction of the fetal ECG signal from the maternal body surface will be seriously interfered by various noises, the most important being the maternal ECG signal (MECG), 50Hz power frequency interference and baseline drift, which will affect the later stage. Analytical ...

AI Technical Summary

Problems solved by technology

The blind signal separation method can detect fetal ECG signals under the assumption that the ECG signals collected by each lead are independent, but it must be carried out under the assumption that the ECG signals collected by each lead are independent and stable, and there are difficulties in modeling. , need a large number of leads and difficult to achieve and other issues

A clearer fetal ECG signal can also be obtained by using two-lead artificial neural network, but the artificial neural network method still needs the assumption that the ECG signal is a stable signal, and the artificial neural network is based on traditional statistics to minimize the fetal ECG signal. Experience risk is the learning goal, and there are many problems to be solved, such as generalization ability, structural design, local extremum, etc.

[0005] Although there are some ECG detection equipment specially designed for fetal ECG detection on the market, fetal ECG monitoring has not been widely used in clinical practice because of the lack of reliable and low-cost methods for indirect detection of fetal ECG signals.

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