Literature DB >> 30666177

An Adaptive Averaging Low Noise Front-End for Central and Peripheral Nerve Recording.

Byunghun Lee1, Maysam Ghovanloo1.   

Abstract

An adaptive averaging low noise analog front-end (AFE) is presented for central and peripheral nerve recording applications. The proposed topology allows users to trade off, on the fly, between input referred noise and the number of channels via averaging. The new low noise amplifier (LNA) utilizes a complementary doubled input transconductance (g m ) topology to effectively increase the noise efficiency factor (NEF) without chopping or use of a costly BiCMOS process. It addresses a disadvantage of the doubled-g m technique by a high input impedance DC-coupled LNA and saves on-chip space for higher density by eliminating AC-coupling capacitors. The proposed technique is particularly suitable for ultra-low noise multichannel recording from the peripheral nervous system (PNS) with channel selection analog multiplexer, where input signal is in tens of μV. A 32-ch proof-of-concept-prototype AFE was fabricated in a 5M2P 130-nm standard CMOS process, occupying 2.4 × 2.5 mm2 together with its control block. The prototype LNA consumes 11 μW from a 1 V supply, providing 3.0 μVrms input referred noise with 61 ΜΩ input impedance, which are desirable for high SNR, to be further improved by the adaptive averaging technique.

Entities:  

Keywords:  Low noise amplifier; closed-loop DC offset rejection; doubled-gm; noise averaging; noise efficiency factor; peripheral nerve recording

Year:  2017        PMID: 30666177      PMCID: PMC6338471          DOI: 10.1109/TCSII.2017.2725988

Source DB:  PubMed          Journal:  IEEE Trans Circuits Syst II Express Briefs        ISSN: 1549-7747            Impact factor:   3.292


  5 in total

1.  An Inductively-Powered Wireless Neural Recording and Stimulation System for Freely-Behaving Animals.

Authors:  Byunghun Lee; Yaoyao Jia; S Abdollah Mirbozorgi; Mark Connolly; Xingyuan Tong; Zhaoping Zeng; Babak Mahmoudi; Maysam Ghovanloo
Journal:  IEEE Trans Biomed Circuits Syst       Date:  2019-01-07       Impact factor: 3.833

2.  A Software-Defined Radio Receiver for Wireless Recording From Freely Behaving Animals.

Authors:  Yaoyao Jia; Byunghun Lee; Fanpeng Kong; Zhaoping Zeng; Mark Connolly; Babak Mahmoudi; Maysam Ghovanloo
Journal:  IEEE Trans Biomed Circuits Syst       Date:  2019-10-24       Impact factor: 3.833

Review 3.  High-density neural recording system design.

Authors:  Han-Sol Lee; Kyeongho Eom; Minju Park; Seung-Beom Ku; Kwonhong Lee; Hyung-Min Lee
Journal:  Biomed Eng Lett       Date:  2022-05-30

Review 4.  Miniaturization for wearable EEG systems: recording hardware and data processing.

Authors:  Minjae Kim; Seungjae Yoo; Chul Kim
Journal:  Biomed Eng Lett       Date:  2022-06-06

5.  A Trimodal Wireless Implantable Neural Interface System-on-Chip.

Authors:  Yaoyao Jia; Ulkuhan Guler; Yen-Pang Lai; Yan Gong; Arthur Weber; Wen Li; Maysam Ghovanloo
Journal:  IEEE Trans Biomed Circuits Syst       Date:  2020-12-31       Impact factor: 3.833

  5 in total

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