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A neural recording amplifier based on adaptive SNR optimization technique for long-term implantation
- A neural recording amplifier based on adaptive SNR optimization technique for long-term implantation
- Lee, Taeju; Jang, Doojin.; Jung, Yoontae; Jeon, Hyuntak; Hong, Soonyoung; Han, Sungmin; Chu, Jun-Uk; Lee, Junghyup; Je, Minkyu
- DGIST Authors
- Lee, Junghyup
- Issue Date
- 2017 IEEE Biomedical Circuits and Systems Conference, BioCAS 2017, 1-4
- 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. © 2017 IEEE.
- Institute of Electrical and Electronics Engineers Inc.
- Related Researcher
Integrated Nano-Systems Lab
Analog and Mixed Signal IC Design; Smart Sensor Systems; Bio-medical ICs and Body Channel Communication Systems
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- Department of Information and Communication EngineeringIntegrated Nano-Systems Lab2. Conference Papers
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