Efficient Self-Adaptive Pseudo-Resistor with Rapid Settling and High Linearity for Neurorecording Front-End Circuits

In this paper, we present a novel self-adaptive pseudo-resistor (A-PR) designed to enhance the performance of neurorecording front-end circuits in terms of settling time, linearity, and tunability. We validate the effectiveness of the proposed A-PR through the implementation of a capacitively- coupled instrumentation amplifier (CCIA) recording front-end using TSMC 40-nm process technology. The results demonstrate that the A-PR enables continuous recording with minimal interruptions, enhancing the system’s robustness and enabling more reliable acquisition of neural signals. Notably, the A-PR achieves a significant reduction in settling time, reaching the millisecond level—1000 times faster than conventional pseudo-resistors—while also exhibiting wide linear characteristics and easy tunability.

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Published
2025-05-25
DOI
https://doi.org/10.1109/iscas56072.2025.11043802
Citations
1
Primary Topic
Advanced Memory and Neural Computing
Type
article
Field-Weighted Citation Impact
0.73

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article

Efficient Self-Adaptive Pseudo-Resistor with Rapid Settling and High Linearity for Neurorecording Front-End Circuits

Jie Yang, Hui Wu, Mohamad Sawan, Yanfei Mao et al.
1 citations
Advanced Memory and Neural Computing
0.73
article

Efficient Self-Adaptive Pseudo-Resistor with Rapid Settling and High Linearity for Neurorecording Front-End Circuits

Jie Yang, Hui Wu, Mohamad Sawan, Yanfei Mao, Xing Liu, Jinbo Chen, Wenjun Zou, Siyu Lin, Xiaofei Kuang, Zheng Tan, Qiming Hou
article en
1 citations

Abstract

In this paper, we present a novel self-adaptive pseudo-resistor (A-PR) designed to enhance the performance of neurorecording front-end circuits in terms of settling time, linearity, and tunability. We validate the effectiveness of the proposed A-PR through the implementation of a capacitively- coupled instrumentation amplifier (CCIA) recording front-end using TSMC 40-nm process technology. The results demonstrate that the A-PR enables continuous recording with minimal interruptions, enhancing the system’s robustness and enabling more reliable acquisition of neural signals. Notably, the A-PR achieves a significant reduction in settling time, reaching the millisecond level—1000 times faster than conventional pseudo-resistors—while also exhibiting wide linear characteristics and easy tunability.

Westlake University (CN), Hangzhou Dianzi University (CN)
Westlake University
Affordable and clean energy
Openalex Percentile: Top 27%
Advanced Memory and Neural Computing
0.73
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Efficient Self-Adaptive Pseudo-Resistor with Rapid Settling and High Linearity for Neurorecording Front-End Circuits — Jie Yang, Hui Wu, et al. · (2025) | TGRS Research Map | TGRS