A hardware-efficient lowpass filter design for biomedical applications

Abstract

A hardware-efficient lowpass filter design technique based on an exponentially weighted moving average (EWMA) filter architecture is proposed for the detection of general action potentials and nerve spikes in noisy signals. The EWMA VLSI architecture is compared with a basic moving average (MA) architecture and it is found that the EWMA technique is the most economical in terms of space of the two. In addition, a rule of thumb is given for converting a MA filter to the proposed filter. In the comparison, it was found that an EWMA filter is almost 85% more hardware-efficient than an MA filter.