Paper Title
Reference Free ANC using Novel Signal Processing Techniques

In this paper, a new process of adaptive artifact elimination from Impedance Cardiography (ICG) signals is proposed. This is a composite model based on wavelet decomposition and adaptive filter. The prime feature of this type methodology is the realization of Adaptive Noise Canceller (ANC) without any reference signal. The proposed model is able to generate a reference signal from the input signal itself with the help of wavelet transforms. In the real time medical environment during critical conditions due to heart rhythm disorders the filter coefficients may become negative. This makes the convergence unbalance, leads to low filtering capability. In order to solve this problem, we incorporate non-negative adaptive algorithms in the proposed ANC. To enhance the performance of ANC, normalization of variants of non-negative least mean square algorithms is adapted to change filter coefficients automatically. Again, in order to minimize computational complexity and to avoid overlapping of data samples at the input stage of the filter a hybrid version of nonnegative and sign based algorithms is considered for implementation. Finally, various ANCs are developed using these algorithms, performance measures are computed and compared. All the implemented ANCs are tested on real impedance cardiogram signals. Index terms - Impedance Cardiography(ICG), Cardiovascular diseases, Adaptive Filter, Wavelet transforms, Adaptive Noise Canceller(ANC),Variants of Non-Negative algorithms.