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32-channel ultra-low-noise arbitrary signal generation platform for biopotential emulation
File | Description | Size | Format | |
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2017_ISCAS_NeuralEmulator_Published.pdf | Accepted version | 5.27 MB | Adobe PDF | View/Open |
Title: | 32-channel ultra-low-noise arbitrary signal generation platform for biopotential emulation |
Authors: | Haci, D Liu, Y Constandinou, TG |
Item Type: | Conference Paper |
Abstract: | This paper presents a multichannel, ultra-low-noise arbitrary signal generation platform for emulating a wide range of different biopotential signals (e.g. ECG, EEG, etc). This is intended for use in the test, measurement and demonstration of bioinstrumentation and medical devices that interface to electrode inputs. The system is organized in 3 key blocks for generating, processing and converting the digital data into a parallel high performance analogue output. These blocks consist of: (1) a Raspberry Pi 3 (RPi3) board; (2) a custom Field Programmable Gate Array (FPGA) board with low-power IGLOO Nano device; and (3) analogue board including the Digital-to-Analogue Converters (DACs) and output circuits. By implementing the system this way, good isolation can be achieved between the different power and signal domains. This mixed-signal architecture takes in a high bitrate SDIO (Secure Digital Input Output) stream, recodes and packetizes this to drive two multichannel DACs, with parallel analogue outputs that are then attenuated and filtered. The system achieves 32-parallel output channels each sampled at 48kS/s, with a 10kHz bandwidth, 110dB dynamic range and uV-level output noise. |
Issue Date: | 28-Sep-2017 |
Date of Acceptance: | 17-Feb-2017 |
URI: | http://hdl.handle.net/10044/1/46113 |
DOI: | 10.1109/ISCAS.2017.8050427 |
Publisher: | IEEE |
Start Page: | 698 |
End Page: | 701 |
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: | Wellcome Trust Engineering & Physical Science Research Council (EPSRC) Engineering & Physical Science Research Council (EPSRC) |
Funder's Grant Number: | BH134389 EP/M020975/1 EP/K015060/1 |
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 |