Aimed at the problem of adaptive noise canceling(ANC),three implementary algorithms which are least mean square(LMS) algorithm,recursive least square(RLS) algorithm and fast affine projection(FAP) algorithm,have been ...Aimed at the problem of adaptive noise canceling(ANC),three implementary algorithms which are least mean square(LMS) algorithm,recursive least square(RLS) algorithm and fast affine projection(FAP) algorithm,have been researched.The simulations were made for the performance of these algorithms.The extraction of fetal electrocardiogram(FECG) is applied to compare the application effect of the above algorithms.The proposed FAP algorithm has obvious advantages in computational complexity,convergence speed and steadystate error.展开更多
This paper deals with detecting fetal electrocardiogram FECG signals from single-channel abdominal lead.It is based on the Convolutional Neural Network(CNN)combined with advanced mathematical methods,such as Independe...This paper deals with detecting fetal electrocardiogram FECG signals from single-channel abdominal lead.It is based on the Convolutional Neural Network(CNN)combined with advanced mathematical methods,such as Independent Component Analysis(ICA),Singular Value Decomposition(SVD),and a dimension-reduction technique like Nonnegative Matrix Factorization(NMF).Due to the highly disproportionate frequency of the fetus’s heart rate compared to the mother’s,the time-scale representation clearly distinguishes the fetal electrical activity in terms of energy.Furthermore,we can disentangle the various components of fetal ECG,which serve as inputs to the CNN model to optimize the actual FECG signal,denoted by FECGr,which is recovered using the SVD-ICA process.The findings demonstrate the efficiency of this innovative approach,which may be deployed in real-time.展开更多
Effective fetal monitoring is an important guarantee for fetal health and early treatment. Fetal movement is one of critical indicators of fetal monitoring, which plays an important role in fetal health. Counting the ...Effective fetal monitoring is an important guarantee for fetal health and early treatment. Fetal movement is one of critical indicators of fetal monitoring, which plays an important role in fetal health. Counting the number of fetal movement by pregnant women is a traditional method for long-term monitoring. However, there are many defects in pregnant women’s feeling count, which cannot meet the accurate requirements of modern perinatal medicine. With the rapid development of biological and electronic technology, various sensors are used to probe the fetal dynamic monitoring, but not on fetal movement. This research proposes a monitoring method for fetal movement via three electrodes. Briefly: first, three electrodes are used to extract electrical signals in the abdomen of pregnant women;second, these signals are amplified and filtered;third, A/D converter with microprocessor is used to make analog digital conversion, which can be stored in the SD card under the control of the microprocessor;finally, the SD card data are processed by computer software and the fetal movement information is analyzed.展开更多
基金the National Key Technologies R&D Program (No. 2006BAI22B01)
文摘Aimed at the problem of adaptive noise canceling(ANC),three implementary algorithms which are least mean square(LMS) algorithm,recursive least square(RLS) algorithm and fast affine projection(FAP) algorithm,have been researched.The simulations were made for the performance of these algorithms.The extraction of fetal electrocardiogram(FECG) is applied to compare the application effect of the above algorithms.The proposed FAP algorithm has obvious advantages in computational complexity,convergence speed and steadystate error.
文摘This paper deals with detecting fetal electrocardiogram FECG signals from single-channel abdominal lead.It is based on the Convolutional Neural Network(CNN)combined with advanced mathematical methods,such as Independent Component Analysis(ICA),Singular Value Decomposition(SVD),and a dimension-reduction technique like Nonnegative Matrix Factorization(NMF).Due to the highly disproportionate frequency of the fetus’s heart rate compared to the mother’s,the time-scale representation clearly distinguishes the fetal electrical activity in terms of energy.Furthermore,we can disentangle the various components of fetal ECG,which serve as inputs to the CNN model to optimize the actual FECG signal,denoted by FECGr,which is recovered using the SVD-ICA process.The findings demonstrate the efficiency of this innovative approach,which may be deployed in real-time.
文摘Effective fetal monitoring is an important guarantee for fetal health and early treatment. Fetal movement is one of critical indicators of fetal monitoring, which plays an important role in fetal health. Counting the number of fetal movement by pregnant women is a traditional method for long-term monitoring. However, there are many defects in pregnant women’s feeling count, which cannot meet the accurate requirements of modern perinatal medicine. With the rapid development of biological and electronic technology, various sensors are used to probe the fetal dynamic monitoring, but not on fetal movement. This research proposes a monitoring method for fetal movement via three electrodes. Briefly: first, three electrodes are used to extract electrical signals in the abdomen of pregnant women;second, these signals are amplified and filtered;third, A/D converter with microprocessor is used to make analog digital conversion, which can be stored in the SD card under the control of the microprocessor;finally, the SD card data are processed by computer software and the fetal movement information is analyzed.
