A software-based platform for multichannel electrophysiological data acquisition

G. Frigo, M. Rubega, G. Lezziero, R. Fontana, C. Cecchetto, S. Vassanelli, G. Sparacino, Matteo Bertocco
{"title":"A software-based platform for multichannel electrophysiological data acquisition","authors":"G. Frigo, M. Rubega, G. Lezziero, R. Fontana, C. Cecchetto, S. Vassanelli, G. Sparacino, Matteo Bertocco","doi":"10.1109/MeMeA.2015.7145227","DOIUrl":null,"url":null,"abstract":"Recent improvements in microelectrodes technology have enabled neuroscientists to record electrophysiological signals from hundreds of neurons and simultaneously from a large number of channels. However, several environmental factors may introduce noise and artefacts and affect proper interpretation of recordings. Thus, the development of appropriate signal acquisition and processing platforms dealing with large data sets and in real-time represents a current fundamental challenge. In the present work, we present an easily-expandable Lab VIEW based software for handling data in real-time during a multichannel neurophysiological signal acquisition. The software was designed to exploit modern MultiCore CPUs for large scale data processing and, by freely setting key acquisition parameters, to work with virtually any kind of biological signal. The software allows for data storage in MATLAB format to facilitate off-line signal processing. Examples of local field potential signal acquisitions from the mouse hippocampus are reported to illustrate software features.","PeriodicalId":277757,"journal":{"name":"2015 IEEE International Symposium on Medical Measurements and Applications (MeMeA) Proceedings","volume":"4 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-05-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 IEEE International Symposium on Medical Measurements and Applications (MeMeA) Proceedings","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MeMeA.2015.7145227","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2

Abstract

Recent improvements in microelectrodes technology have enabled neuroscientists to record electrophysiological signals from hundreds of neurons and simultaneously from a large number of channels. However, several environmental factors may introduce noise and artefacts and affect proper interpretation of recordings. Thus, the development of appropriate signal acquisition and processing platforms dealing with large data sets and in real-time represents a current fundamental challenge. In the present work, we present an easily-expandable Lab VIEW based software for handling data in real-time during a multichannel neurophysiological signal acquisition. The software was designed to exploit modern MultiCore CPUs for large scale data processing and, by freely setting key acquisition parameters, to work with virtually any kind of biological signal. The software allows for data storage in MATLAB format to facilitate off-line signal processing. Examples of local field potential signal acquisitions from the mouse hippocampus are reported to illustrate software features.
基于软件的多通道电生理数据采集平台
最近微电极技术的改进使神经科学家能够同时记录来自数百个神经元和大量通道的电生理信号。然而,一些环境因素可能会引入噪音和人工制品,并影响录音的正确解释。因此,开发适当的信号采集和处理平台来处理大数据集和实时是当前的一个基本挑战。在目前的工作中,我们提出了一个易于扩展的基于Lab VIEW的软件,用于在多通道神经生理信号采集过程中实时处理数据。该软件旨在利用现代多核cpu进行大规模数据处理,并通过自由设置关键采集参数,几乎可以处理任何类型的生物信号。该软件允许以MATLAB格式存储数据,方便离线信号处理。本文报道了从小鼠海马体获取局部场电位信号的例子,以说明软件的特点。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信