Cited by 78Analog and Mixed-Signal Circuit DesignNeuroscience and Neural EngineeringRadio Frequency Integrated Circuit Design

Design of a low-noise preamplifier for nerve cuff electrode recording

Rieger, R., Taylor, J., Demosthenous, A., Donaldson, N., Langlois, P.J.·2003·IEEE Journal of Solid-State Circuits

Abstract

This paper discusses certain important issues involved in the design of a nerve signal preamplifier for implantable neuroprostheses. Since the electroneurogram signal measured from cuff electrodes is typically on the order of 1 μV, a very low-noise interface is essential. We present the argument for the use of BiCMOS technology in this application and then describe the design and evaluation of a complete preamplifier fabricated in a 0.8-μm double-metal double-poly process. The preamplifier has a nominal voltage gain of 100, a bandwidth of 15 kHz, and a measured equivalent input-referred noise voltage spectral density of 3.3 nV//spl radic/Hz at 1 kHz. The total input-referred rms noise voltage in a bandwidth 1 Hz-10 kHz is 290 nV, the power consumption is 1.3 mW from ±2.5-V power supplies, and the active area is 0.3 mm2.

Integrity signals

Registry

Crossref · 10.1109/jssc.2003.814437

Cites

20 of 20 references verified0 citation errors · 0 not checkable

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  • Amplifier noise is typically designed to be lower than electrode noise and is maintained below 5 μVrms for CNS-recording amplifiers and below 1 μVrms for PNS-recording amplifiers.

    “The noise introduced by the amplifier is typically designed to be lower than that introduced by the electrodes and, for a majority of neural applications, is maintained below 5 µVrms for amplifiers used to record CNS signals and less than 1 µVrms for PNS-recording amplifiers [76, 105].”
  • CNS-based neuroprostheses, or brain-machine interfaces, decode neural electrical activity to control robotic limbs or to stimulate muscles for restoring limb function.

    “CNS-based neuroprostheses, or brain–machine interfaces (BMIs), are systems whereby neural electrical activities are decoded and used to control robotic limbs [76, 89, 105] or to stimulate muscles for restoring limb function [35].”

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Authors
Rieger, R., Taylor, J., Demosthenous, A., Donaldson, N., & Langlois, P. J.
Affiliations
  • University College London (GB)
  • University of Bath (GB)
Venue
IEEE Journal of Solid-State Circuits
Published
2003-08
Volume
38
Issue
8
Pages
1373-1379
ISSN
0018-9200 (ISSN-L)
OpenAlex
W2059054388
Cited by
78
References
20
Citations by year
2026: 1 · 2024: 3 · 2022: 1 · 2021: 1 · 2020: 7 · 2019: 1 · 2018: 2 · 2017: 3 · 2016: 4 · 2014: 5 · 2013: 3 · 2012: 2
FWCI
5.27
Type
journal article
Language
en
Open access
closed
Locations
  • IEEE Journal of Solid-State Circuits (publishedVersion)
  • UCL Discovery (University College London) (submittedVersion)
Topics
  • Physical Sciences › Engineering › Biomedical Engineering › Analog and Mixed-Signal Circuit Design
  • Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Neuroscience and Neural Engineering
  • Physical Sciences › Engineering › Electrical and Electronic Engineering › Radio Frequency Integrated Circuit Design
Keywords
low-noise preamplifier, cuff electrodes, electroneurogram, BiCMOS, input-referred noise, neural recording, low-power analog circuits

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