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Artifacts removal from ECG signal using an ANFIS technique

An artifact cancellation with adaptive neuro-fuzzy inference system (ANFIS) is introduced for denoising ECG signal. ECG signal detection has been commonly used by individuals and doctors inside and outside the clinic to diagnose cardiac diseases. For the correct diagnosis, artifacts removal that they affect the quality of ECG signal becomes needful. In this paper, the ANFIS method is firstly applied to suppress the power line interference and the baseline wander artifacts from corrupted ECG signal then the outputs of the proposed method are compared with the outputs of methods such as LMS (least mean Square) and NLMS (Normalized Least Mean Square). Based on our experiments that were performed on the number of ECG signals, it was shown that the proposed ANFIS method can significantly detect and remove the artifacts.