A Chopped Neural Front-End Featuring Input Impedance Boosting With Suppressed Offset-Induced Charge Transfer

Modern neuromodulation systems typically provide a large number of recording and stimulation channels, which reduces the available power and area budget per channel. To maintain the necessary input-referred noise performance despite growingly rigorous area constraints, chopped neural front-ends are often the modality of choice, as chopper-stabilization allows to simultaneously improve (1/f) noise and area consumption. The resulting issue of a drastically reduced input impedance has been addressed in prior art by impedance boosters based on voltage buffers at the input. These buffers precharge the large input capacitors, reduce the charge drawn from the electrodes and effectively boost the input impedance. Offset on these buffers directly translates into charge-transfer to the electrodes, which can accelerate electrode aging. To tackle this issue, a voltage buffer with ultra-low time-averaged offset is proposed, which cancels offset by periodic reconfiguration, thereby minimizing unintended charge transfer. This article explains the background and circuit design in detail and presents measurement results of a prototype implemented in a 180 nm HV CMOS process. The measurements confirm that signal-independent, buffer offset induced charge transfer occurs and can be mitigated by the presented buffer reconfiguration without adversely affecting the operation of the input impedance booster. The presented neural recorder front-end achieves state of the art performance with an area consumption of
${0.036}\,{{\rm {mm}}^2}$
, an input referred noise of
${1.32}\,\mu {\rm {V}}_{\text{rms}}$
(1 to 200 Hz) and
${3.36}\,\mu {\rm {V}}_{\text{rms}}$
(0.2 to 10 kHz), power consumption of
${13.7}\,{\mu {\rm W}}$
from 1.8 V supply, as well as CMRR and PSRR
$\ge$
83 dB at 50 Hz.