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An ECG, SQA plays an important role in significantly improving the performance. However, in real cases, artifacts often corrupt. In this paper, several methods have been analyzed for ECG enhancement like fast Fourier transforms (FFT), empirical mode decomposition (EMD) and Hilbert vibration decomposition (HVD) based filtering. These methods are able to remove both high frequency and baseline wander noises. The method is validated through experiments on the PhysioNet/MITBIHA database records. Techniques are compared in terms of correlation, SNR and detection error rate. The simulation shows that the HVD-based filtering method provides a very good result for denoising and BW removal. In addition, we analyzed two types of SQA algorithms features and rules-based method and filtering and threshold-based signal quality assessment methods, which are intended to assess reliable heart rates and the good quality of ECG signal. The proposed methods are well suited for transmitting valid data for cloud diagnosis. |
