A common method to eliminate unwanted power line interference in neurobiology laboratories where sensitive electronic signals are measured is with a notch filter. However a fixed-frequency notch filter cannot remove all power line noise contamination since inherent frequency and phase variations exist in the contaminating signal. One way to overcome the limitations of a fixedfrequency notch filter is with adaptive noise cancellation. Adaptive noise cancellation is an active approach that uses feedback to create a signal that when summed with the contaminated signal destructively interferes with the noise component leaving only the desired signal. We have implemented an optimized least mean square adaptive noise cancellation algorithm on a lowcost 16 MHz, 8-bit microcontroller to adaptively cancel periodic 60 Hz noise. In our implementation, we achieve between 20 and 25 dB of cancellation of the 60 Hz noise component.
Low-Cost, High-Fidelity, Adaptive Cancellation of Periodic 60 Hz Noise,
Journal of Neuroscience Methods 185 (2009) 50–55 (pdf)
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