A neural recording amplifier based on adaptive SNR optimization technique for long-term implantation

2017 IEEE Biomedical Circuits and Systems Conference (BioCAS) Pub Date : 2017-10-20 DOI:10.1109/BIOCAS.2017.8325150

Taeju Lee, Doojin Jang, Yoontae Jung, Hyuntak Jeon, Soonyoung Hong, Sungmin Han, Jun-Uk Chu, Junghyup Lee, M. Je

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引用次数: 4

Abstract

Long-term neural recording which can consistently provide good signal-to-noise ratio (SNR) performance over time is important for stable operation of neuroprosthetic systems. This paper presents an analysis for the SNR optimization in a changing environment which causes variations in the tissue-electrode impedance, Zte. Based on the analysis result, a neural recording amplifier (NRA) is developed employing the SNR optimization technique. The NRA can adaptively change its configuration for in situ SNR optimization. The SNR is improved by 4.69% to 23.33% as Zte changes from 1.59 MQ to 31.8 MQ at 1 kHz. The NRA is fabricated in a 0.18-μm standard CMOS process and operates at 1.8-V supply while consuming 1.6 μA It achieves an input-referred noise of 4.67 μVrms when integrated from 1 Hz to 10 kHz, which leads to the NEF of 2.27 and the NEF2VDD of 9.28. The frequency reponse is measured with a high-pass cutoff frequency of 1 Hz and a low-pass cutoff frequency of 10 kHz. The midband gain is set to 40 dB while occupying 0.11 mm2 of a chip area.

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基于自适应信噪比优化技术的长期植入神经记录放大器

长期的神经记录能够持续地提供良好的信噪比(SNR)性能，对于神经修复系统的稳定运行至关重要。本文介绍了在变化的环境中SNR优化的分析，这种环境会导致组织电极阻抗的变化。在分析结果的基础上，采用信噪比优化技术研制了一种神经记录放大器。NRA可以自适应地改变其配置以进行现场信噪比优化。当中兴通讯在1 kHz时从1.59 MQ变为31.8 MQ时，信噪比提高了4.69%至23.33%。该NRA采用0.18 μm标准CMOS工艺，工作电压为1.8 v，功耗为1.6 μA，在1 Hz ~ 10 kHz范围内集成时，输入参考噪声为4.67 μVrms, NEF为2.27,NEF2VDD为9.28。频率响应测量的高通截止频率为1hz，低通截止频率为10khz。中频增益设置为40 dB，同时占用0.11 mm2的芯片面积。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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2017 IEEE Biomedical Circuits and Systems Conference (BioCAS)

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