In this paper some effective noise cancellers were proposed using the variants of Least Mean Fourth (LMF) Algorithm to remove the artifacts that occur during the acquisition stage of an ECG signal. In order to accelerate the performance of the LMF algorithm we introduce data normalization in weight update process. This results two variants of LMF algorithm, called normalized LMF (NLMF) and global NLMF (GNLMF) algorithms. Further, to minimize their computational complexity and improve convergence characteristics, tracking ability, filtering capability we apply signum and block processing on the two versions of normalized algorithms. Both the two treatments results six more algorithms. Using these algorithms we develop various adaptive noise cancellers (ANCs). These ANCs are tested with the help of standard MIT-BIH arrhythmia database for various records. The Signal to noise ratio, Excess Mean Square Error and misadjustment are taken as performances measures to analyze the performance of proposed methods. These ANCs exhibit improved performance over the LMF based ANC.