FECG (Fetal ECG) signal contains potentially precise information that could assist clinicians in making more appro-priate and timely decisions during pregnancy and labor. The extraction and detection of the FECG signa...FECG (Fetal ECG) signal contains potentially precise information that could assist clinicians in making more appro-priate and timely decisions during pregnancy and labor. The extraction and detection of the FECG signal from com-posite maternal abdominal signals with powerful and advance methodologies is becoming a very important requirement in fetal monitoring. The purpose of this paper is to illustrate the developed algorithms on FECG signal extraction from the abdominal ECG signal using Neural Network approach to provide efficient and effective ways of separating and understanding the FECG signal and its nature. The FECG signal was isolated from the abdominal signal by neural network approach with different learning constant value and momentum as well so that acceptable signal can be con-sidered. According to the output it can be said that the algorithm is working satisfactory on high learning rate and low momentum value. The method appears to be exceedingly robust, correctly isolate the FECG signal from abdominal ECG.展开更多
Foetus ECG monitoring based on Bluetooth portable devices promise to provide an efficient, accurate, and economic way to monitor foetus health outside the hospital. In this paper we discuss a new idea in biomedical fi...Foetus ECG monitoring based on Bluetooth portable devices promise to provide an efficient, accurate, and economic way to monitor foetus health outside the hospital. In this paper we discuss a new idea in biomedical field may be useful for Medical services. The idea is deliver the status of patent to any location within the coverage of cellular networks, such as the global system for mobile (GSM) communications. Pregnancy women from a rural area just like rural in Sudan(where they haven’t transportation to a hospital), could be given a routine check by mobile phone without having to commute regularly to a hospital. Routine inspections and monitoring could be done while the pregnancy women is at home, traveling(nomadic), at work, or at leisure, thereby relieving resources for more demanding hospital cases. Advances in mobile technology have made wireless telemedicine more practical both within hospitals and globally. The Bluetooth system with low cost the poor women can use and also has low electromagnetic waves, it is healthy in use (no risk).展开更多
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
文摘FECG (Fetal ECG) signal contains potentially precise information that could assist clinicians in making more appro-priate and timely decisions during pregnancy and labor. The extraction and detection of the FECG signal from com-posite maternal abdominal signals with powerful and advance methodologies is becoming a very important requirement in fetal monitoring. The purpose of this paper is to illustrate the developed algorithms on FECG signal extraction from the abdominal ECG signal using Neural Network approach to provide efficient and effective ways of separating and understanding the FECG signal and its nature. The FECG signal was isolated from the abdominal signal by neural network approach with different learning constant value and momentum as well so that acceptable signal can be con-sidered. According to the output it can be said that the algorithm is working satisfactory on high learning rate and low momentum value. The method appears to be exceedingly robust, correctly isolate the FECG signal from abdominal ECG.
文摘Foetus ECG monitoring based on Bluetooth portable devices promise to provide an efficient, accurate, and economic way to monitor foetus health outside the hospital. In this paper we discuss a new idea in biomedical field may be useful for Medical services. The idea is deliver the status of patent to any location within the coverage of cellular networks, such as the global system for mobile (GSM) communications. Pregnancy women from a rural area just like rural in Sudan(where they haven’t transportation to a hospital), could be given a routine check by mobile phone without having to commute regularly to a hospital. Routine inspections and monitoring could be done while the pregnancy women is at home, traveling(nomadic), at work, or at leisure, thereby relieving resources for more demanding hospital cases. Advances in mobile technology have made wireless telemedicine more practical both within hospitals and globally. The Bluetooth system with low cost the poor women can use and also has low electromagnetic waves, it is healthy in use (no risk).
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.