DocumentCode
865455
Title
Very Low-Noise ENG Amplifier System Using CMOS Technology
Author
Rieger, Robert ; Schuettler, Martin ; Pal, Dipankar ; Clarke, Chris ; Langlois, Peter ; Taylor, John ; Donaldson, Nick
Author_Institution
Dept. of Electr. Eng., Nat. Sun Yat-Sen Univ., Kaohsiung
Volume
14
Issue
4
fYear
2006
Firstpage
427
Lastpage
437
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 muV, very low-noise, high-gain amplifiers are required. The ten-channel system we describe was realized in a 0.8 mum 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 mm2 and the power consumption is 24 mW from plusmn2.5 V power supplies
Keywords
CMOS integrated circuits; amplifiers; bioelectric potentials; biomedical electrodes; neurophysiology; prosthetics; 0.8 mum; 1 Hz to 5 kHz; 2.5 V; 24 mW; CMOS technology; action potential velocity; electroneurographic signals; multielectrode nerve cuff; very low-noise ENG amplifier system; Bandwidth; CMOS technology; Electric variables measurement; Energy consumption; In vitro; Low-noise amplifiers; Root mean square; Signal design; System testing; Time measurement; Multielectrode cuff; nerve cuff; tripolar recording; Action Potentials; Amplifiers; Computer-Aided Design; Diagnostic Techniques, Neurological; Electrodes, Implanted; Equipment Design; Equipment Failure Analysis; Microelectrodes; Peripheral Nerves; Reproducibility of Results; Semiconductors; Sensitivity and Specificity;
fLanguage
English
Journal_Title
Neural Systems and Rehabilitation Engineering, IEEE Transactions on
Publisher
ieee
ISSN
1534-4320
Type
jour
DOI
10.1109/TNSRE.2006.886731
Filename
4032757
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