Improved PID based Adaptive Controllers for Denoising Biomedical Signals

Abstract

Biomedical signal processing is one of the most popular research domains. Very fine features in biomedical signals carry important information regarding patient’s health. So, it is necessary to have noise free biomedical signals for the correct diagnosis. The major trouble for biomedical equipment is Power Line Interference (PLI) which impairs the signals. An adaptive filter can be one of the possible solutions for the removal of non-stationary noise, but maintaining the system stability along with a high convergence rate is a critical issue. The adaptive algorithm works on the principle of minimization of error for optimized coefficients updating while PID controller attempts to minimize the error over time by adjusting the control variables. In this paper, these two different approaches are combined to get an efficient solution for adaptive PLI cancellation and two new algorithms namely PID-based Response Adjustment for Reducing Error (PID-RARE) and PID-based Coefficient Adjustment for Reducing Error (PID-CARE) are proposed. The integration of NSLMS adaptive algorithm with PID controller in the proposed algorithms are found to be an effective solution to adaptive PLI cancellation and have shown quite better performance in terms of SNRout, correlation coefficient, mean square error thereby providing more cleaner signal at lesser convergence rate.