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CAD for the Detection of Fetal Electrocardiogram through Neuro-Fuzzy Logic and Wavelets Systems for Telemetry

机译:通过神经模糊逻辑和小波遥测系统检测胎儿心电图的CAD

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Telemetry is used for sensing and measuring of information at some location and then to transmit to desire location. It is very useful for medical monitoring too. The electrical activity of heart is measured in the form of electrocardiogram (ECG) at skin. The monitoring of fetus ECG(FECG) is important to monitor the baby inside mom abdomen. The observation during labour and delivery is done by monitoring fetus heart rate(FHR). The abdominal electrocardiogram(AECG) consist of FECG as well as maternal electrocardiogram(MECG). The amplitude of FECG is very less in compare to MECG. So its difficult to separate. In this paper we use orthogonal frequency division multiplexing (OFDM) for transmission from remote area with high signal to noise ratio(SNR). Wavelet transforms (WT) and artificial intelligence systems is used to de-noise composite signal and to obtain FCEG from AECG. Coding is done in MATLAB and computer added diagnosis(CAD) is used to avoid any mistakes. The artificial neural network and fuzzy interference system (ANFIS) is used to get exact F-ECG at desired location.
机译:遥测技术用于感测和测量某个位置的信息,然后传输到所需的位置。这对于医疗监控也非常有用。心脏的电活动以皮肤上的心电图(ECG)形式进行测量。胎儿心电图(FECG)的监测对于监测妈妈腹部内的婴儿非常重要。分娩和分娩期间的观察是通过监测胎儿心率(FHR)进行的。腹部心电图(AECG)由FECG以及孕妇心电图(MECG)组成。与MECG相比,FECG的幅度要小得多。因此其难以分离。在本文中,我们使用正交频分复用(OFDM)从具有高信噪比(SNR)的偏远地区进行传输。小波变换(WT)和人工智能系统用于对复合信号进行消噪并从AECG获得FCEG。编码是在MATLAB中完成的,并且使用计算机添加的诊断程序(CAD)来避免任何错误。人工神经网络和模糊干扰系统(ANFIS)用于在所需位置获得精确的F-ECG。

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