@inproceedings{25ca32ea4a1f46e98462cb8dcd79df6f,
title = "A 340nW/channel neural recording analog front-end using replica-biasing LNAs to tolerate 200mvpp interfere from 350MV power supply",
abstract = "This paper presents an 8-channel power-efficient neural recording analog front-end (AFE) with high power-supply rejection ratio (PSRR) and wide dynamic range. The ultra-low power is achieved by using a low supply voltage current-reusing input stage in the low noise amplifier (LNA). In order to improve the PSRR in low supply voltage amplifiers, we propose a replica biasing circuit to generate the biasing current, which is insensitive to the supply noise. Furthermore, the dynamic range is enlarged by utilizing an averaged local field potential (A-LFP) feedback loop. The prototype is fabricated in a 65nm CMOS process. Each channel of the AFE occupies 0.04mm2 and only consumes 340nW from 0.35V/0.7V dual supply. The AFE provides a maximum gain of 54dB with 6.7μV input-referred noise integrating from 0.5Hz to 6.5 kHz. The proposed 0.35V input stage can tolerate a supply interferer up to 200mVpp, while maintaining a PSRR of 74dB.",
keywords = "Active potential, Local field potential, Low noise, Low power, Neural recorder, PSRR",
author = "Liangjian Lyu and Dawei Ye and \{Richard Shi\}, \{C. J.\}",
note = "Publisher Copyright: {\textcopyright} 2019 IEEE; 2019 IEEE International Symposium on Circuits and Systems, ISCAS 2019 ; Conference date: 26-05-2019 Through 29-05-2019",
year = "2019",
doi = "10.1109/ISCAS.2019.8702781",
language = "英语",
series = "Proceedings - IEEE International Symposium on Circuits and Systems",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "2019 IEEE International Symposium on Circuits and Systems, ISCAS 2019 - Proceedings",
address = "美国",
}