Adaptive algorithms for real-time filtering of electrocardiogram with multilevel noise estimation - Тулякова, Н.О.; Трофимчук, О.М. (Radiotekhnika, 2020)
Non-stationary noise with a varying and previously unknown level of variance in time, an example of which is electromyographic (EMG) noise, often contaminates a signal of an electrocardiogram (ECG). Ensuring high quality filtering of non-stationary noise in the ECG is necessary, since its presence significantly reduces the accuracy of measurements, complicates or makes it impossible to use recognition and classification algorithms and making reliable diagnostic decisions, accordingly. An adaptive method of suppression of non-stationary noise in ECG with noise and signal-dependent switching of component filters by increasing the number of noise levels for their estimation has been further developed in this study. On the basis of the method improved in this way, the one-, two-, and three-pass algorithms and an algorithm with re-filtering dependent on preliminary noise estimates are designed. As components of the method, it is proposed to use simple and optimal Savitzky-Golay and moving averaging filters. Statistical estimates of efficiency are obtained by numerical simulations using such criteria as mean-square error and signal-to-noise ratio for a ECG model signal sampled at 1 kHz and the output signals of the adaptive algorithms under different additive Gaussian noise conditions have shown improvements in filtering quality. There are no distortions in the QRS complex at very low noise. The high efficiency of noise suppression at different levels of its variance and the advantage of re-filtering are demonstrated. The filter applying to the ECG signal with the real EMG noise confirms high quality of non-stationary noise suppression and of ECG waves preservation and the advantage over high-effective dynamic filtering also. The proposed adaptive algorithms do not require complex computational operations and are quick, i.e. allow real-time signal processing (with little delay in obtaining a current sample of output signal with respect to the corresponding sample of the signal at the input of filtering algorithm).