A 2 $\mu\hbox{W}$ 100 nV/rtHz Chopper-Stabilized Instrumentation Amplifier for Chronic Measurement of Neural Field Potentials

TLDR

Neural field potentials are low‑amplitude, low‑bandwidth signals reflecting the collective activity of thousands of neurons, making them vulnerable to noise and necessitating high‑fidelity measurement. The authors aim to present a prototype micropower instrumentation amplifier for chronic measurement of neural field potentials. The amplifier is a chopper‑stabilized, 0.8‑µm CMOS circuit that consumes under 2 µW, incorporates an on‑chip high‑pass filter to suppress electrode offsets, and eliminates 1/f and popcorn noise. The device achieves a 0.98 µVrms noise floor (0.05–100 Hz) with a noise‑efficiency factor of 4.6, the lowest reported, and its low‑power, monolithic design could support neuroprosthetics and seizure monitoring.

Abstract

This paper describes a prototype micropower instrumentation amplifier intended for chronic sensing of neural field potentials (NFPs). NFPs represent the ensemble activity of thousands of neurons and code-useful information for both normal activity and disease states. NFPs are small - of the order of tens of muV- and reside at low bandwidths that make them susceptible to excess noise. Therefore, to ensure the highest fidelity of signal measurement for diagnostic analysis, the amplifier is chopper-stabilized to eliminate 1/f and popcorn noise. The circuit was prototyped in an 0.8 mum CMOS process and consumes under 2.0 muW from a 1.8 V supply. A noise floor of 0.98 muVrms was achieved over a bandwidth from 0.05 to 100 Hz; the noise-efficiency factor of 4.6 is one of the lowest published to date. A flexible on-chip high-pass filter is used to suppress front-end electrode offsets while maintaining relevant physiological data. The monolithic architect and micropower low-noise low-supply operation could help enable applications ranging from neuroprosthetics to seizure monitors that require a small form factor and battery operation. Although the focus of this paper is on neurophysiological sensing, the circuit architecture can be applied generally to micropower sensor interfaces that benefit from chopper stabilization.