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.
Authors
- Jie Yang (ORCID: https://orcid.org/0000-0002-4148-0042)
- Hui Wu (ORCID: https://orcid.org/0009-0001-4079-068X)
- Mohamad Sawan (ORCID: https://orcid.org/0000-0002-4137-7272)
- Yanfei Mao (ORCID: https://orcid.org/0000-0002-5075-1377)
- Xing Liu (ORCID: https://orcid.org/0009-0009-3659-6663)
- Jinbo Chen (ORCID: https://orcid.org/0000-0001-6202-9165)
- Wenjun Zou (ORCID: https://orcid.org/0000-0002-3231-9281)
- Siyu Lin (ORCID: https://orcid.org/0000-0001-8726-943X)
- Xiaofei Kuang (ORCID: https://orcid.org/0009-0007-3269-8254)
- Zheng Tan
- Qiming Hou
Institutions
- Westlake University (CN)
- Hangzhou Dianzi University (CN)
Publication Details
- 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
Funders
- Westlake University