An Improved Pseudo-Resistor with Well-Biased Technique and Proportional Calibration Technique for Neural Amplifiers

Pseudo-resistors are widely used in neural amplifiers to generate a very low cut-off frequency and avoid DC offset while recording neural signals. However, conventional pseudo-resistors suffer from process variation, temperature variation and body leakage problems, leading to neural amplifier saturation and even instability. To solve these problems, an improved pseudo-resistor is designed with a well-biased technique to minimize the body leakage current and with the proportional calibration technique to achieve process and temperature robustness. The improved pseudo-resistor could achieve a $208.997 \mathrm{G} \Omega$ at 1000 Hz with 8.3% process variation and with mean crossed voltage(caused by body leakage current) 19.1 mV with 0.97% process variation within three standard deviations. The improved pseudo-resistor’s resistance varies by 3.4% and crossed voltage varies by 10 mV with the temperature from $0^{\circ} \mathrm{C}$ to $100^{\circ} \mathrm{C}$. As proof of concept, a capacitively coupled neural amplifier with this improved pseudo-resistor is also designed for testing. This work is designed using a 65 nm process.

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Published
2024-10-24
DOI
https://doi.org/10.1109/biocas61083.2024.10798401
Citations
1
Primary Topic
Neural Networks and Applications
Type
article
Field-Weighted Citation Impact
0.35

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article

An Improved Pseudo-Resistor with Well-Biased Technique and Proportional Calibration Technique for Neural Amplifiers

Hung Chun Li, Yanyan Xu, Sio Hang Pun, Baijun Zhang et al.
1 citations
Neural Networks and Applications
0.35
article

An Improved Pseudo-Resistor with Well-Biased Technique and Proportional Calibration Technique for Neural Amplifiers

Hung Chun Li, Yanyan Xu, Sio Hang Pun, Baijun Zhang, Zhen Yuan, Liyang Wang, Ruihan Zheng, Yu Xia, Hong Liang Loo
article en
1 citations

Abstract

Pseudo-resistors are widely used in neural amplifiers to generate a very low cut-off frequency and avoid DC offset while recording neural signals. However, conventional pseudo-resistors suffer from process variation, temperature variation and body leakage problems, leading to neural amplifier saturation and even instability. To solve these problems, an improved pseudo-resistor is designed with a well-biased technique to minimize the body leakage current and with the proportional calibration technique to achieve process and temperature robustness. The improved pseudo-resistor could achieve a $208.997 \mathrm{G} \Omega$ at 1000 Hz with 8.3% process variation and with mean crossed voltage(caused by body leakage current) 19.1 mV with 0.97% process variation within three standard deviations. The improved pseudo-resistor’s resistance varies by 3.4% and crossed voltage varies by 10 mV with the temperature from $0^{\circ} \mathrm{C}$ to $100^{\circ} \mathrm{C}$. As proof of concept, a capacitively coupled neural amplifier with this improved pseudo-resistor is also designed for testing. This work is designed using a 65 nm process.

Sun Yat-sen University (CN), University of Macau (MO)
Technology Development, Research and Development
Affordable and clean energy
Openalex Percentile: Top 30%
Neural Networks and Applications
0.35
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An Improved Pseudo-Resistor with Well-Biased Technique and Proportional Calibration Technique for Neural Amplifiers — Hung Chun Li, Yanyan Xu, et al. · (2024) | TGRS Research Map | TGRS