• Robert Rieger, Martin Schuettler, Dipankar Pal, Chris Clarke, Peter Langlois, John Taylor, and Nick Donaldson.
• Department of Electrical Engineering, National Sun Yat-sen University, Taiwan.
• IEEE Trans Neural Syst Rehabil Eng. 2006 Dec 1; 14 (4): 427-37.

AbstractIn 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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