Noise Reduction from Electrocardiogram Signal Using Signal Processing Techniques

The Electrocardiogram (ECG) represents over a period of time the electric activity of cardiac muscle. The rhythmic contraction of the heart is continual. ECG analysis is highly important for diagnosing heart problems. 

The ECG signals are usually influenced by many forms of sound, such as baseline wandering (BLW), power line interference (PLI), motion artifacts, noise in electromyography (EMG), instruments, etc. 

A comparison analysis has here been made of artifacts from the corrupted ECG signal between window-based filtering and adaptive filtering technology. In terms of signal to noise ratio (SNR), mean square error (MSE), the performance study was performed 

Keywords: ECG signal, adaptive filter algorithm, Window Based filter, SNR, MSE, PRD