Continuous-time acquisition of biosignals using a charge-based ADC topology
File(s)
Accepted version
Author(s)
Maslik, Michal
Liu, Yan
Lande, Tor Sverre
Constandinou, TG
Type
Journal Article
Abstract
This paper investigates continuous-time (CT) signal acquisition as an activity-dependent and nonuniform sampling alternative to conventional fixed-rate digitisation. We demonstrate the applicability to biosignal representation by quantifying the achievable bandwidth saving by nonuniform quantisation to commonly recorded biological signal fragments allowing a compression ratio of ≈5 and 26 when applied to electrocardiogram and extracellular action potential signals, respectively. We describe several desirable properties of CT sampling, including bandwidth reduction, elimination/reduction of quantisation error, and describe its impact on aliasing. This is followed by demonstration of a resource-efficient hardware implementation. We propose a novel circuit topology for a charge-based CT analogue-to-digital converter that has been optimized for the acquisition of neural signals. This has been implemented in a commercially available 0.35 μm CMOS technology occupying a compact footprint of 0.12 mm 2 . Silicon verified measurements demonstrate an 8-bit resolution and a 4 kHz bandwidth with static power consumption of 3.75 μW from a 1.5 V supply. The dynamic power dissipation is completely activity-dependent, requiring 1.39 pJ energy per conversion.
Date Issued
2018-06-01
Date Acceptance
2018-02-27
Citation
IEEE Transactions on Biomedical Circuits and Systems, 2018, 12 (3), pp.471-482
ISSN
1932-4545
Publisher
Institute of Electrical and Electronics Engineers
Start Page
471
End Page
482
Journal / Book Title
IEEE Transactions on Biomedical Circuits and Systems
Volume
12
Issue
3
Copyright Statement
© 2018 IEEE. Personal use is permitted, but republication/redistribution requires IEEE permission.
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standards/publications/rights/index.html for more information.
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License URL
Sponsor
Engineering & Physical Science Research Council (EPSRC)
Engineering & Physical Science Research Council (EPSRC)
Engineering & Physical Science Research Council (EPSRC)
Identifier
https://ieeexplore.ieee.org/document/8359012
Grant Number
EP/M020975/1
EP/I000569/1
EP/I000569/1
Subjects
Science & Technology
Technology
Engineering, Biomedical
Engineering, Electrical & Electronic
Engineering
Analogue-to-Digital Converter
Biosignals
Continuous-Time
CT-ADC
EAP
ECG
LFP
LEVEL-CROSSING ADC
Humans
Signal Processing, Computer-Assisted
Humans
Signal Processing, Computer-Assisted
0903 Biomedical Engineering
0906 Electrical and Electronic Engineering
Electrical & Electronic Engineering
Publication Status
Published
Date Publish Online
2018-05-15