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Title A Low-power Neural Signal Acquisition Analog Front-end IC for Closed-loop Neural Interfaces
Authors (Donghoon Choi) ; (Hyouk-Kyu Cha)
DOI https://doi.org/10.5573/JSTS.2022.22.5.368
Page pp.368-375
ISSN 1598-1657
Keywords Analog front-end IC; neural recording amplifier; programmable gain amplifier; stimulation artifact
Abstract This paper presents an ultra-low-power neural signal recording analog front-end IC (AFE) which is comprised of a low-noise amplifier (LNA) followed by a programmable gain amplifier (PGA). To achieve good overall performance while handling stimulation artifacts in closed-loop neural interface systems, the proposed LNA is designed for moderate gain, low input noise, and, good linearity while the PGA is included for additional gain and tunable bandwidth functions. Implemented using 0.18-μm CMOS process, the AFE achieves a measured closed-loop gain of 20 to 40 dB and integrated input referred noise of 3.39 μVrms over 1 Hz to 6.5 kHz. The IC consumes 1.49 μW at 1-V supply and the noise efficiency factor is 1.93. For less than 1% total harmonic distortion, the AFE can accommodate up to 60 mVpp and 280 mVpp of differential and common-mode stimulation artifacts, respectively.