Experimental investigation of denoising electrocardiogram using lagrange form of hermite interpolating polynomial with chebyshev nodes

Analysis of ECG for detecting different cardiovascular diseases requires real-time ECG signals which are acquired by attaching electrodes to the body. During the ECG signal acquisition, noise gets added to original signal, which might distort the morphological features, like amplitude, segment length and the interval aspects of the ECG leading to a false diagnosis and improper interpretation of cardiovascular disease. Therefore, ECG denoising is imperative. Here, we propose approximation using hermite polynomial interpolation with chebyshev nodes for denoising electrocardiogram signals that consequently compresses them too. Recommended algorithm is applied on twelve ECG signals taken from MIT-BIH arrhythmia database without any additional noise as the signals are already corrupted with noise. Performance of the proposed algorithm is evaluated using various performance metrics. Experimental results prove that the proposed method efficiently denoises electrocardiogram signals and gives quite encouraging results when compared with other existing denoising and compression algorithms.