Robust Cancellation of EEG from the Surface of ECG by using Modified Linear Iterative Kalman Filter
نویسندگان
چکیده
In Bio-medical engineering, Electrocardiograph (ECG) has a key importance to diagnose the heart diseases. While acquiring the ECG signal, an Electroencephalography (EEG) interferes the desired ECG signal, due to which the true information can not be retrieved. In this paper, the modified Iterative Version of Adaptive kalman and Recursive Least Square (RLS) Adaptive Filtering algorithms are used to cancel out the affects of EEG from the surface of ECG signal. Simulation results show that the Modified version of Iterative Kalman algorithm provides robustness as well as good tracking performance than RLS filtering algorithm. Keywords— Modified iterative Kalman, recursive least square (RLS), Electrocardiograph (ECG), Electroencephalography (EEG).
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