Volume 9, Issue 4 (December 2013)                   IJEEE 2013, 9(4): 224-231 | Back to browse issues page

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Ghorbani-Nejad A, Jannesari A. A Sub-µW Tuneable Switched-Capacitor Amplifier-Filter for Neural Recording Using a Class-C Inverter. IJEEE 2013; 9 (4) :224-231
URL: http://ijeee.iust.ac.ir/article-1-568-en.html
A Sub-µW Tuneable Switched-Capacitor Amplifier-Filter for Neural Recording Using a Class-C Inverter
A Ghorbani-Nejad , A Jannesari
Abstract:   (5166 Views)
A two stage sub-µW Inverter-based switched-capacitor amplifier-filter is presented which is capable of amplifying both spikes and local field potentials (LFP) signals. Here we employ a switched capacitor technique for frequency tuning and reducing of 1/f noise of two stages. The reduction of power consumption is very necessary for neural recording devices however, in switched capacitor (SC) circuits OTA is a major building block that consumes most of the power. Therefore an OTA-less technique utilizing a class-C inverter is employed that significantly reduces the power consumption. A detailed analysis of noise performance for the inverter-based SC circuits is presented. A mathematical model useful for analysis of such SC integrators is derived and a good comparison is obtained between simulation and analytical technique. With a supply voltage of 0.7V and using 0.18 µm CMOS technology, this design can achieves a power consumption of about 538 nW. The designed amplifier-filter has the gains 18.6 dB and 28.2 dB for low pass only and cascaded filter, respectively. By applying different sampling frequencies, the filter attains a reconfigurable bandwidth.
Keywords: Amplifier-Filter , Inverter-Based Switched-Capacitor Circuit , Neural Recording
Full-Text [PDF 789 kb]   (3022 Downloads)    
Type of Study: Research Paper | Subject: Integrated Circuits: Digital, Analog
Received: 2013/04/13 | Revised: 2014/09/16 | Accepted: 2013/12/22
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Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
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© 2022 by the authors. Licensee IUST, Tehran, Iran. This is an open access journal distributed under the terms and conditions of the Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) license.