A Neural Recording Amplifier Based on Adaptive SNR Optimization Technique for Long-Term Implantation

Title
A Neural Recording Amplifier Based on Adaptive SNR Optimization Technique for Long-Term Implantation
Authors
한성민Taeju LeeDoojin JangYoontae JungHyuntak JeonSoonyoung HongJun-Uk ChuJunghyup LeeMinkyu Je
Keywords
Long-term neural recording; foreign body reaction; signal-to-noise ratio optimization; adaptive neural recording amplifier
Issue Date
2017-10
Publisher
IEEE Biomedical Circuits and Systems Conference 2017
Citation
-355
Abstract
Vrms 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.; 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 tissueelectrode 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 M to 31.8 M at 1 kHz. The NRA is fabricated in a 0.18- m standard CMOS process and operates at 1.8-V supply while consuming 1.6  A. It achieves an input-referred noise of 4.67 &#61549
URI
http://pubs.kist.re.kr/handle/201004/66340
Appears in Collections:
KIST Publication > Conference Paper
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