Normalized Least Means Square (NLMS) Adaptive Algorithm as an Effective Method for Denoising Real Time ECG Signal

Electrocardiogram (ECG) signals play a crucial role in the diagnosis of a range of cardiac disorders; however, they are frequently affected by various sources of noise, including baseline drift, muscle movements, electrode displacement, and electrical interference from power lines.This study introduces a robust adaptive filtering method founded on the Normalized Least Mean Squares (NLMS) algorithm, designed to effectively remove noise from ECG signals while retaining key diagnostic characteristics.The proposed methodology dynamically adjusts filter coefficients in realtime, successfully mitigating both high-frequency and low-frequency noise elements without altering essential waveform components, including the P-wave, QRS complex, and T-wave.To establish