A New Method for ECG Denoising Using an Amalgamation of Adaptive and SG Filters

Since ECG signals are non-stationary physiological, the recorded signals are corrupted by varied noise resources. So, they cannot be used to diagnose the illness. Separating signals from undesired noise such as motion artifact, power-line interference (PLI), and baseline wander (BW), is the main problem when analyzing medical data. These destructive effects are more severe, especially during the patient's physical activity. The objective of this research is to find effective ways to remove anomalies in the cardiac signal. In this paper, a method for noise reduction has been presented. In this regard, the noise reduction from heart signal, is improved using an amalgamation adaptive and Savitsky-Golay filter. Also, the presented ANC is modified by combining with a SG filter as suggested ECG noise cancelation (A-S) system. Findings demonstrate that the suggested A-S is more accurate and adequate compared to the previous methods.