An analog integrated front-end amplifier for neural applications

Zhijun Zhou; Paul Warr

doi:10.1109/ICAM.2016.7813579

An analog integrated front-end amplifier for neural applications

Zhijun Zhou, Paul Warr

Research output: Chapter in Book/Report/Conference proceeding › Conference Contribution (Conference Proceeding)

1 Citation (Scopus)

399 Downloads (Pure)

Abstract

The front-end amplifier forms the critical element for signal detection and pre-processing within neural monitoring systems. It determines not only the fidelity of the biosignal, but also impacts power consumption and detector size. In this paper, a combined feedback loop-controlled approach is proposed to neutralize for the input leakage currents generated by low noise amplifiers when in integrated circuit form, alongside signal leakage into the input bias network. Significantly, this loop topology ensures the front-end amplifier maintains a high input impedance across all manufacturing and operational variations. Furthermore, this feedback loop provides the amplification for the low amplitude neural signals without significant increase in power consumption or input-referred noise.

Original language	English
Title of host publication	Proceedings of 2016 IEEE International Conference on Integrated Circuits and Microsystems, ICICM 2016
Publisher	Institute of Electrical and Electronics Engineers (IEEE)
Pages	135-139
Number of pages	5
ISBN (Electronic)	9781509028146
ISBN (Print)	9781509028139
DOIs	https://doi.org/10.1109/ICAM.2016.7813579
Publication status	Published - 16 Jan 2017
Event	2016 IEEE International Conference on Integrated Circuits and Microsystems, ICICM 2016 - Chengdu, China Duration: 23 Nov 2016 → 25 Nov 2016

Conference

Conference	2016 IEEE International Conference on Integrated Circuits and Microsystems, ICICM 2016
Country/Territory	China
City	Chengdu
Period	23/11/16 → 25/11/16

Keywords

analog integrated circuits
biomedical signal processing
CMOS technology
Low-noise amplifiers
neural recording

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10.1109/ICAM.2016.7813579

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Cite this

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abstract = "The front-end amplifier forms the critical element for signal detection and pre-processing within neural monitoring systems. It determines not only the fidelity of the biosignal, but also impacts power consumption and detector size. In this paper, a combined feedback loop-controlled approach is proposed to neutralize for the input leakage currents generated by low noise amplifiers when in integrated circuit form, alongside signal leakage into the input bias network. Significantly, this loop topology ensures the front-end amplifier maintains a high input impedance across all manufacturing and operational variations. Furthermore, this feedback loop provides the amplification for the low amplitude neural signals without significant increase in power consumption or input-referred noise.",

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Zhou, Z & Warr, P 2017, An analog integrated front-end amplifier for neural applications. in Proceedings of 2016 IEEE International Conference on Integrated Circuits and Microsystems, ICICM 2016., 7813579, Institute of Electrical and Electronics Engineers (IEEE), pp. 135-139, 2016 IEEE International Conference on Integrated Circuits and Microsystems, ICICM 2016, Chengdu, China, 23/11/16. https://doi.org/10.1109/ICAM.2016.7813579

An analog integrated front-end amplifier for neural applications. / Zhou, Zhijun; Warr, Paul.

Proceedings of 2016 IEEE International Conference on Integrated Circuits and Microsystems, ICICM 2016. Institute of Electrical and Electronics Engineers (IEEE), 2017. p. 135-139 7813579.

Research output: Chapter in Book/Report/Conference proceeding › Conference Contribution (Conference Proceeding)

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ER -

An analog integrated front-end amplifier for neural applications

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