  Electrocardiogram (ECG) signals can frequently be affected by the
introduction of noise and artifacts. Since these types of signal corruptions
disrupt the accurate interpretation of ECG signals, noise and artifacts must be
eliminated during the preprocessing phase. In this paper, we introduced a
comprehensive pre-processing phase that eliminates motion artifacts and noise
prior to detecting and extracting entirely corrupted ECG signal segments. The
first method, denoted as the WLNH method, is constructed using wavelet
multiresolution analysis (MRA), the Lillifors test, NLM, and a high-pass
filter. The second method entails substituting the wavelet MRA decomposition
with the variational mode decomposition (VMD) while retaining all other stages
from the first method. This technique is denoted as the VLWNH. The two proposed
methods differ from some existing methods in that they first employ the
Lilliefors test to identify whether a component is white Gaussian noise and
then utilize the High Pass Filter to eliminate motion anomalies. The simulation
results show that the offered solutions are effective, particularly when
dealing with white Gaussian noise and base-line wander (BW) noise.
