A Non-Linearities Based Noise Canceler for Cardiac Signal Enhancement in Wireless Health Care Monitoring

In this paper, we present a computationally low complex Dead Zone Signed Regressor LMS (DZSRLMS) algorithm, that can be applied to ECG signal in order to remove various artifacts from them. This algorithm enjoys less computational complexity because of the sign present in the algorithm and good filtering capability because of the threshold applied to error signal. As a result it is particularly suitable for applications requiring large signal to noise ratios with less computational complexity such as wireless biotelemetry. The DZSRLMS algorithm mostly employs simple addition and shift operations and achieves considerable speed up over the LMS algorithm. Simulation studies shows that the proposed realization gives better performance compared to existing realizations in terms of signal to noise ratio.