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Fetal electrocardiogram extraction system based on convolutional encoding-decoding neural network and method

A neural network and fetal ECG technology, applied in medical science, sensors, diagnostic recording/measurement, etc., can solve problems such as fetal ECG extraction interference

Inactive Publication Date: 2020-07-21
SUN YAT SEN UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

One of the difficulties in extracting the fetal ECG signal is that the abdominal electrical signal contains the mother's ECG component, which usually has a larger amplitude than the fetus, and the mother's ECG component and the fetus' ECG component are in time. Both domain and frequency domain overlap, so it brings great interference to the extraction of fetal ECG

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  • Fetal electrocardiogram extraction system based on convolutional encoding-decoding neural network and method
  • Fetal electrocardiogram extraction system based on convolutional encoding-decoding neural network and method
  • Fetal electrocardiogram extraction system based on convolutional encoding-decoding neural network and method

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Embodiment 1

[0058] Embodiment 1 (a kind of fetal electrocardiogram extraction system based on convolution codec neural network)

[0059] A fetal electrocardiogram extraction system based on convolution codec neural network, comprising the following devices:

[0060] Data collection device: used to collect the abdominal electrical signal of a pregnant woman;

[0061] Maternal ECG component estimation device: It is used to predict the maternal ECG component in the abdominal electrical signal of pregnant women by using the convolution codec neural network, that is, the simulated abdominal electrical signal is used as the input of the neural network during training, and the simulated abdominal electrical signal The maternal ECG components are used as network labels for training, and the trained convolution codec neural network is obtained; when measuring the real fetal ECG components, the real single-channel maternal abdominal electrical signals are input into the trained convolution codec I...

Embodiment 2

[0076] Embodiment 2 (a kind of fetal electrocardiogram extraction method based on convolution codec neural network)

[0077] Such as figure 1 As shown, the present invention provides a method for extracting fetal electrocardiogram based on convolution codec neural network, comprising the following steps:

[0078] Data preprocessing: collecting abdominal electrical signals of pregnant women;

[0079] Maternal ECG component estimation: The convolution codec neural network is used to estimate the maternal ECG component in the abdominal electrical signal of pregnant women, that is, the simulated abdominal electrical signal is used as the input of the neural network during training, and the maternal ECG component in the abdominal electrical signal is simulated. The ECG component is used as a network label for training, and the real single-channel pregnant woman's abdominal electrical signal is used as the input of the neural network during the test, and the output of the neural ne...

Embodiment 3

[0082] Embodiment 3 (a kind of fetal electrocardiogram extraction method based on convolution codec neural network)

[0083] The following describes the implementation process of the above-mentioned basic implementation manner in conjunction with a specific implementation manner. However, this embodiment is only used to illustrate the technical solution, and does not represent a limitation on the protection scope of the technical solution.

[0084] A method for extracting fetal electrocardiogram based on convolution codec neural network, comprising the following steps:

[0085] 1) Data preprocessing: First, if image 3 As shown, the electrode is used to collect a signal on the abdomen of the mother, and the sampling frequency is 250Hz. Again, the signal is filtered with a bandpass filter with a passband of 0.5-100Hz and a 50Hz notch filter. Secondly, an amplifier circuit is used The signal is amplified and the electrical signal is converted into a digital signal with an anal...

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Abstract

The invention discloses a fetal electrocardiogram extraction system based on convolutional encoding-decoding neural network and a method thereof. The system comprises a data collection device, a maternal electrocardiograph component estimation device, and a fetal electrocardiograph component extraction device. The data collection device is for collecting a real abdominal electrical signal of a pregnant woman. The maternal electrocardiograph component estimation device is for using a convolutional encoding-decoding neural network to estimate a maternal electrocardiograph component in the abdominal electrical signal of the pregnant woman; in training, an analog abdominal electrical signal is input into a neural network and a maternal electrocardiograph component in the analog abdominal electrical signal serves as a network label; and in testing, the real abdominal electrical signal of the pregnant woman is input into the neural network and the estimated maternal electrocardiograph component in the abdominal electrical signal is output by the neural network. The fetal electrocardiograph component extraction device is for subtracting the obtained maternal electrocardiograph component from the collected abdominal electrical signal of the pregnant woman to extract a fetal electrocardiograph component from the collected abdominal electrical signal of the pregnant woman. The method comprises the steps of data pre-processing, estimation of the maternal electrocardiograph component and extraction of the fetal electrocardiograph component. Through the technical scheme, the efficiencyand accuracy of fetal electrocardiograph extraction can be effectively improved.

Description

technical field [0001] The present invention relates to the technical field of fetal electrocardiogram extraction, in particular to a fetal electrocardiogram extraction system based on a convolution codec neural network, and further provides a method for using the system. Background technique [0002] Fetal heart rate monitoring is a means of fetal intrauterine monitoring, which can reflect the biophysical activity of the fetus in real time, and is widely used in clinical practice. play an important role in reducing perinatal mortality. The perinatal mortality rate reflects the comprehensive economic development and health care status of a country and region to some extent. [0003] Fetal ECG signals can not only be used to calculate the fetal heart rate, but also provide more morphological information, which records the movement of the fetal heart and objectively reflects the various states of fetal intrauterine physiological activities. It can judge the development degre...

Claims

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Application Information

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IPC IPC(8): A61B5/0444A61B5/344
CPCA61B5/7264A61B5/344
Inventor 王国利钟伟郭雪梅
Owner SUN YAT SEN UNIV
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