Abstract:
Electrocardiogram (ECG) is the graphical illustration of heart activity to diagnose various
cardiovascular diseases. Presence of Power Line Interference (PLI) in ECG makes it difficult for
the examiner to identify proper working of heart. To remove such interference different types of
adaptive noise cancellers have been implemented. All the adaptive algorithms previously
implemented for such purpose have either better convergence, mean square error (MSE) or better
complexity. So a new algorithm named SSLMS is implemented to have a compromise between
the previously mentioned parameters. Using SSLMS, first impulsive component of PLI has been
removed and comparison of it has been made with NLMS, RLS and SSRLS algorithms. In later
work, PLI having known frequency is estimated using sinusoidal model of SSLMS algorithm and
comparisons are made with SSRLS algorithm. Later PLI with unknown frequency is being tracked
by first converging to its true frequency and then estimating it based to the new value of frequency.
In the end PLI with unidirectional and bidirectional frequency is being estimated and removed
from ECG signal. Moreover, every simulation using SSLMS has also been compared with those
of SSRLS algorithm. As SSRLS has better convergence and MSE but exceptionally high
computational complexity than that of SSLMS algorithm, so a new hybrid algorithm is proposed
that combines the best features of both SSRLS and SSLMS algorithms. This algorithm has faster
convergence than that of SSLMS algorithm and lower computational complexity than SSRLS
algorithm. Moreover, its MSE is lower than those of both SSRLS and SSLMS algorithm.
Simulation results prove the enhanced performance of the proposed hybrid.
