Reduction Noise of ECG Signal Using Extended Kalman Filter

The Electrocardiogram (ECG) signal is one of the recognizing approaches to discover heart disease. One of the major difficulties in biomedical data processing like electrocardiography is the separation of the original signal from noises affected by body movement and respiration, electromagnetic field, power line and high frequency interference. Various methods of digital filters are exploited to delete signal parts from unnecessary frequency ranges. It is hard to use filters with constant coefficients to reduction random noises, as human behavior is not accurate known depending on the time. Adaptive filter method is needed to overcome this difficulty. In this paper the Extended Kalman Filter is applied and proposed for ECG signal modeling and noise reduction, the results of simulations in Maltab are presented. The results show that the EKF output is capable to track the original ECG signal form even in the noisiest period of the ECG signal. Keyword-ECG signal, Extended Kalman Filter, Denosing, noise reduction, ECG simulator.