Literature DB >> 17190035

Very low-noise ENG amplifier system using CMOS technology.

Robert Rieger1, Martin Schuettler, Dipankar Pal, Chris Clarke, Peter Langlois, John Taylor, Nick Donaldson.   

Abstract

In this paper, we describe the design and testing of a system for recording electroneurographic signals (ENG) from a multielectrode nerve cuff (MEC). This device, which is an extension of the conventional nerve signal recording cuff, enables ENG to be classified by action potential velocity. In addition to electrical measurements, we provide preliminary in vitro data obtained from frogs that demonstrate the validity of the technique for the first time. Since typical ENG signals are extremely small, on the order of 1 1 microV, very low-noise, high-gain amplifiers are required. The ten-channel system we describe was realized in a 0.8 microm CMOS technology and detailed measured results are presented. The overall gain is 10 000 and the total input-referred root mean square (rms) noise in a bandwidth 1 Hz-5 kHZ is 291 nV. The active area is 12 mm(2) and the power consumption is 24 mW from +/-2.5 V power supplies.

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Year:  2006        PMID: 17190035     DOI: 10.1109/TNSRE.2006.886731

Source DB:  PubMed          Journal:  IEEE Trans Neural Syst Rehabil Eng        ISSN: 1534-4320            Impact factor:   3.802


  5 in total

1.  The theory of velocity selective neural recording: a study based on simulation.

Authors:  John Taylor; Martin Schuettler; Chris Clarke; Nick Donaldson
Journal:  Med Biol Eng Comput       Date:  2012-02-24       Impact factor: 2.602

2.  Noise and selectivity of velocity-selective multi-electrode nerve cuffs.

Authors:  N Donaldson; R Rieger; M Schuettler; J Taylor
Journal:  Med Biol Eng Comput       Date:  2008-08-12       Impact factor: 2.602

3.  An implantable ENG detector with in-system velocity selective recording (VSR) capability.

Authors:  Chris Clarke; Robert Rieger; Martin Schuettler; Nick Donaldson; John Taylor
Journal:  Med Biol Eng Comput       Date:  2016-09-16       Impact factor: 2.602

Review 4.  Implantable neurotechnologies: a review of integrated circuit neural amplifiers.

Authors:  Kian Ann Ng; Elliot Greenwald; Yong Ping Xu; Nitish V Thakor
Journal:  Med Biol Eng Comput       Date:  2016-01-22       Impact factor: 2.602

Review 5.  Recent advances in neural recording microsystems.

Authors:  Benoit Gosselin
Journal:  Sensors (Basel)       Date:  2011-04-27       Impact factor: 3.576

  5 in total

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