Removal of ECG Noise Artifacts Using Signal Processing Techniques

ECG is considered to be the most vital physiological parameter for examining the anatomic and physiologic facets of the heart muscles. It is a graphical trace providing the electrical activity of the heart and is thus keenly used for clinical diagnosis. But over time, the ECG signals tend to change their statistical properties and hence are referred to have non-stationary behavior. Since the tools used in ECG recordings are based on analog circuitry, in certain exhausting and peripatetic conditions, the recorded ECG is contaminated with various types of noise artifacts. The main artificial artifacts include power-line interference, baseline drift and electrode contact noise. The main biological artifacts are motion artifacts and muscles artifacts (EMG noise). This paper presents an approach to filter the noise artifacts in the ECG signal and thus facilitate the detection of the QRS complex using the adaptive threshold. The experimental results also present the evaluation parameters before and after filtering of the ECG signal.