Abstract
SUMMARY This paper describes a low-noise and low-power spike neural signal amplifier design that has cut-off frequency compensation between channels and chips. The variation of the frequency characteristics of amplifiers should be minimized among the channels and chips. This is a requirement to perform statistical correlation analysis from a neuroscience-oriented point of view. Our design includes an adjustable cut-off frequency using a 4-bit variable capacitance. After compensation, the variation of the cut-off frequency was reduced to between -0.4 kHz and +0.3 kHz from between -1.1 kHz and +3.6 kHz; that is, the value before trimming under the condition of a target cut-off frequency of 10 kHz. We designed a multineural signal amplifier using the Rohm 0.18 μm CMOS process. The designed neural amplifier has capacitive coupled differential input to reject large dc offsets generated at the electrode-tissue interface and to avoid strong common mode noise. To achieve high energy efficiency with low noise in order to observe spike signals of the order of a few tens of mV, the MOS transistors in the OTA are operated in the subthreshold region and combined with a low-pass filter that consumes less than a hundred nW. The amplifier yielded a midband gain of 37.9 dB and the input-referred noise was measured as 3.76 μVrms with a consumption of 4.30 μW, with a ±0.9 V power supply. These results correspond to a noise efficiency factor (NEF) of 2.23, close to the limit using a single differential OTA prepared by a CMOS process.
Original language | English |
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Pages (from-to) | 62-73 |
Number of pages | 12 |
Journal | Electronics and Communications in Japan |
Volume | 99 |
Issue number | 5 |
DOIs | |
Publication status | Published - 2016 May 1 |
Keywords
- CMOS LSI
- bio-signal
- cut-off frequency variation
- low-noise low-power design
- neural signal amplifier
ASJC Scopus subject areas
- Signal Processing
- Physics and Astronomy(all)
- Computer Networks and Communications
- Electrical and Electronic Engineering
- Applied Mathematics