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A charge-based ultra-low power continuous-time ADC for data driven neural spike processing

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Title: A charge-based ultra-low power continuous-time ADC for data driven neural spike processing
Authors: Maslik, M
Liu, Y
Lande, TS
Constandinou, TG
Item Type: Conference Paper
Abstract: The paper presents a novel topology of a continuous-time analogue-to-digital converter (CT-ADC) featuring ultra-low static power consumption, activity-dependent dynamic consumption, and a compact footprint. This is achieved by utilising a novel charge-packet based threshold generation method, that alleviates the requirement for a conventional feedback DAC. The circuit has a static power consumption of 3.75uW, with dynamic energy of 1.39pJ/conversion level. This type of converter is thus particularly well-suited for biosignals that are generally sparse in nature. The circuit has been optimised for neural spike recording by capturing a 3kHz bandwidth with 8-bit resolution. For a typical extracellular neural recording the average power consumption is in the order of ~4uW. The circuit has been implemented in a commercially available 0.35um CMOS technology with core occupying a footprint of 0.12 sq.mm
Issue Date: 28-Sep-2017
Date of Acceptance: 17-Feb-2017
URI: http://hdl.handle.net/10044/1/46112
DOI: 10.1109/ISCAS.2017.8050620
Publisher: IEEE
Start Page: 1420
End Page: 1423
Journal / Book Title: 2017 IEEE International Symposium on Circuits and Systems (ISCAS)
Copyright Statement: © 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Sponsor/Funder: Engineering & Physical Science Research Council (EPSRC)
Wellcome Trust
Funder's Grant Number: EP/M020975/1
BH134389
Conference Name: IEEE International Symposium on Circuits and Systems (ISCAS)
Keywords: Science & Technology
Technology
Engineering, Electrical & Electronic
Engineering
Publication Status: Published
Start Date: 2017-05-28
Finish Date: 2017-05-31
Conference Place: Baltimore, MD (USA)
Online Publication Date: 2017-09-28
Appears in Collections:Electrical and Electronic Engineering
Faculty of Engineering