Adaptive Notch Filter for EEG Signals Based on the LMS Algorithm with Variable Step-Size Parameter

This paper presents the use of an adaptive noise canceler (ANC) with variable step-size parameter for the elimination of power line interference in the recording of EEG signals within the relatively unexplored gamma-band (35100 Hz). The use of an adaptive step-size parameter offers a balance in terms of convergence, misadjustment, and rejection bandwidth optimization. Simulation results are presented to support the proposed algorithm and compare its performance with fixed step-size ANC schemes. It will be shown that the proposed algorithm outperforms classical fixed step-size ANC algorithms and eliminates the cumbersome trial and error process needed to choose an adequate value for such parameter.

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