Low-power linear-phase delay filters for neural signal processing: Comparison and synthesis

We present the design and implementation of linear-phase delay filters for ultra-low power neural signal processing. The filters are intended to implement a low-distortion delay element for automatic biopotential detection in neural recording implants. Continuous-time OTA-C filters are used to realize a 9^th-order equiripple transfer function presenting a constant group delay. This analog delay allows to process neural waveforms with reduced overhead compared with digital delays. An allpass transfer function is used to implement such analog delay because it achieves wider constant-delay bandwidth than all-pole does. Two filters realizations are compared for implementing it: the cascaded structure and the inverse follow-the-leader feedback filter. Their respective strengths and drawbacks are assessed by modeling parasitics and non-idealities of OTAs, and using transistor-level simulations. A power budget of 200 nA is used in both filters. Experimental measurements with the chosen topology are presented and discussed.