Noise Reduction from Electrocardiogram Signal Using Signal Processing Techniques

The electrocardiogram (ECG) is the physical representation of electrical activities of heart muscles over a period of time. It is generated by continuous rhythmic contraction of heart. Analysis of ECG is very essential to diagnose cardiac issues. Usually ECG signal is affected by different types of noises like base line wander (BLW), power line interference (PLI), motion artifacts, electromyography (EMG) noise, instrumentation noise etc. Here in this paper a comparative study has been done between window based filtering technique and adaptive filtering technique to remove artifact from contaminated ECG signal. The performance analysis has been carried out in terms of signal to noise ratio (SNR), mean square error (MSE) and root mean square difference (%PRD value).