Removing undesirable artifacts in electrocardiogram signals is essential for biological signal processing as the signal gets distorted and makes appropriate investigation challenging. A primary source of distortion affecting recordings is the 50Hz power line interference. To get a high-quality recording, we used a filtering method based on an efficient decomposition technique known as variational mode extraction. This approach is similar to the variational mode decomposition methodology but with a few alterations in mathematical computation. First, it extracts the noise efficiently in a specific frequency band. Then, we apply the discrete wavelet transform to the signal, employing soft thresholding. As a result, it eliminates the extra noise and filters the electrocardiogram signal. We evaluated the efficacy of our proposed method using an arrhythmia database. Furthermore, we compared recent decomposition methods on six random signals using signal-to-noise ratios, mean square errors, correlation coefficients, and other signal features. Our method also efficiently eliminates varying amplitude of powerline noise and finally outperforms decomposition strategies regarding noise reduction and processing complexity across all signal parameters.