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ECG(electrocardiogram) Digital Signal Processing for the Biomedical Applications

机译:ECG(心电图)生物医学应用的数字信号处理

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With the development of the internet of things (IoT) and well spread telecommunication application, a new system of ECG (electrocardiogram) is proposed with a portable device and adding advance telemedicine service. ECG is recorded with the help of graphical phenomenon to observe the electrical activity of the heart. At the time of recording no noise should be taken because it interferes with the original signals and make changes that is why it’s mandatory to avoid the noise signals. To estimate the level of noise in the ECG signal processing pipeline is very important because it provides fair measurements. When the level of noise is much higher, it is needed to be used the noise suppression. Also, the proper estimation of noise level can be utilized guide the adaptive filtering process by controlling the strength of filtering in accordance with the noise level estimation in the ECG signals. Therefore the delineation combined algorithm is preferred to avoid the mismatch of their load. It is also a vital decision about the interval quality to separate the intervals of EMG (electromyography) signals from the noise. The ECG is now demonstrated a dominant heart bit signal and the SNR is higher in our proposed model.
机译:随着事物互联网(物联网)和良好的传播电信应用,提出了一种新的ECG(心电图)系统,具有便携式设备并加入预先远程杂皮物服务。在图形现象的帮助下记录ECG以观察心脏的电气活动。在录制时,不应采取噪音,因为它会干扰原始信号并进行更改,这就是为什么强制以避免噪声信号。为了估计ECG信号处理管道中的噪声水平非常重要,因为它提供了公平的测量。当噪声水平高得多时,需要使用噪声抑制。此外,可以利用根据ECG信号中的噪声电平估计来控制滤波强度来指导自适应滤波处理的正确估计。因此,划定组合算法是优选的,以避免其负荷不匹配。对于间隔质量来分离来自噪声的EMG(肌电学)信号的间隔是一种重要的决定。 ECG现在展示了主导心脏比特信号,并且我们提出的模型中的SNR更高。

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