Improvement of ECG Signal Noise Removal Using Recursive Kalman Filter

Nowadays، Kalman filter has been wildly used for solving the problem of real world. Kalman filter is a recursive filter that estimates the state of a linear dynamic system from a series of noisy measurements. One of the applications of Kalman filter is signal processing. In this paper، we use Kalman filter for electrocardiogram (ECG) signal noise removal. First accidental ECG signals are collected from Physiobank database and then Kalman filter is tuned for noise removing from ECG signals. In addition، we apply Finite Impulse Response (FIR) filter for ECG signal noise removing and finally we compare the performance of two filters using Mean Square Error (MSE) measurement. Results show the superior performance of Kalman filter for ECG signal noise removal.