如何在22nm FDSOI中设计神经记录系统的输入级

Franz Marcus Schüffny, S. Höppner, S. Zeinolabedin, R. George, C. Mayr
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引用次数: 1

摘要

在现代基于电极的神经记录系统中,记录通道的增加受到功率的限制。新兴的CMOS技术,如22纳米FDSOI,由于其在数字电路集成中的特殊能效,有望在克服功率限制方面开辟新的前景,然而,它们也对此类系统的模拟前端级提出了挑战,特别是在信号噪声方面。本文讨论了低噪声放大器(LNA)的设计,这是该技术和应用中最关键的功率和噪声器件。此外,还描述了振荡噪声和闪烁噪声之间的权衡,这导致了LNA运算放大器的设计,在给定电流下最小化噪声。电容器类型的泄漏不同,因此噪声也不同。因此,我们模拟和分析了不同类型和尺寸的直流去耦电容器,以估计LNA的最小面积要求。值得注意的是,在该技术中,所描述的设计接近给定电流和输入电容的最小输入参考噪声。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
How to design an input stage for neural recording system in 22 nm FDSOI
The increase of recording channels in modern electrode-based neural recording systems is limited by considerations of power. Emerging CMOS technologies like 22 nm FDSOI promise to open new perspectives in overcoming power constraints due to their particular energy efficiency in digital circuit integration, they however also pose a challenge for the analogue front-end stages of such systems, especially with respect to signal noise. This paper addresses the design of low noise amplifiers (LNA), the most critical component with respect to power and noise, in this technology and application. Moreover, a trade-off between igs-shot noise and flicker noise is described, which leads to the design of the LNA’s operational amplifier, minimising noise for a given current. Capacitor types vary in leakage and hence in noise. We therefore simulated and analysed different types and sizes of DC-decoupling capacitors for an estimation of the minimum-area requirement of the LNA. Notably, the described design approaches the minimum input-referred noise possible for a given current and input capacitor in this technology.
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