A charge-based ultra-low power continuous-time ADC for data driven neural spike processing
File(s)2017_ISCAS_NeuralTracker_Published.pdf (2.55 MB)
Accepted version
Author(s)
Maslik, M
Liu, Y
Lande, TS
Constandinou, TG
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
Date Issued
2017-09-28
Date Acceptance
2017-02-17
Citation
2017 IEEE International Symposium on Circuits and Systems (ISCAS), 2017, pp.1420-1423
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
Engineering & Physical Science Research Council (EPSRC)
Wellcome Trust
Grant Number
EP/M020975/1
BH134389
Source
IEEE International Symposium on Circuits and Systems (ISCAS)
Subjects
Science & Technology
Technology
Engineering, Electrical & Electronic
Engineering
Publication Status
Published
Start Date
2017-05-28
Finish Date
2017-05-31
Coverage Spatial
Baltimore, MD (USA)
Date Publish Online
2017-09-28