An ultra-low power dual-mode ECG monitor for healthcare and wellness

Daniele Bortolotti, Mauro Mangia, Andrea Bartolini, R. Rovatti, G. Setti, L. Benini
{"title":"An ultra-low power dual-mode ECG monitor for healthcare and wellness","authors":"Daniele Bortolotti, Mauro Mangia, Andrea Bartolini, R. Rovatti, G. Setti, L. Benini","doi":"10.7873/DATE.2015.0784","DOIUrl":null,"url":null,"abstract":"Technology scaling enables today the design of ultra-low cost wireless body sensor networks for wearable biomedical monitors. These devices, according to the application domain, show greatly varying tradeoffs in terms of energy consumption, resources utilization and reconstructed biosignal quality. To achieve minimal energy operation and extend battery life, several aspects must be considered, ranging from signal processing to the technological layers of the architecture. The recently proposed Rakeness-based Compressed Sensing (CS) expands the standard CS paradigm deploying the localization of input signal energy to further increase data compression without sensible RSNR degradation. This improvement can be used either to optimize the usage of a non volatile memory (NVM) to store in the device a record of the biosignal or to minimize the energy consumption for the transmission of the entire signal as well as some of its features. We specialize the sensing stage to achieve signal qualities suitable for both Healthcare (HC) and Wellness (WN), according to an external input (e.g. the patient). In this paper we envision a dual-operation wearable ECG monitor, considering a multi-core DSP for input biosignal compression and different technologies for either transmission or local storage. The experimental results show the effectiveness of the Rakeness approach (up to ≈ 70% more energy efficient than the baseline) and evaluate the energy gains considering different use case scenarios.","PeriodicalId":162450,"journal":{"name":"2015 Design, Automation & Test in Europe Conference & Exhibition (DATE)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-03-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"26","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 Design, Automation & Test in Europe Conference & Exhibition (DATE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.7873/DATE.2015.0784","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 26

Abstract

Technology scaling enables today the design of ultra-low cost wireless body sensor networks for wearable biomedical monitors. These devices, according to the application domain, show greatly varying tradeoffs in terms of energy consumption, resources utilization and reconstructed biosignal quality. To achieve minimal energy operation and extend battery life, several aspects must be considered, ranging from signal processing to the technological layers of the architecture. The recently proposed Rakeness-based Compressed Sensing (CS) expands the standard CS paradigm deploying the localization of input signal energy to further increase data compression without sensible RSNR degradation. This improvement can be used either to optimize the usage of a non volatile memory (NVM) to store in the device a record of the biosignal or to minimize the energy consumption for the transmission of the entire signal as well as some of its features. We specialize the sensing stage to achieve signal qualities suitable for both Healthcare (HC) and Wellness (WN), according to an external input (e.g. the patient). In this paper we envision a dual-operation wearable ECG monitor, considering a multi-core DSP for input biosignal compression and different technologies for either transmission or local storage. The experimental results show the effectiveness of the Rakeness approach (up to ≈ 70% more energy efficient than the baseline) and evaluate the energy gains considering different use case scenarios.
用于医疗保健和健康的超低功耗双模式ECG监护仪
今天,技术扩展使可穿戴生物医学监视器的超低成本无线身体传感器网络的设计成为可能。根据应用领域的不同,这些设备在能量消耗、资源利用和重建的生物信号质量方面表现出很大不同的权衡。为了实现最小的能量运行并延长电池寿命,必须考虑几个方面,从信号处理到架构的技术层。最近提出的基于rakeness的压缩感知(CS)扩展了标准的CS范式,部署了输入信号能量的局部化,以进一步提高数据压缩,而不会明显降低RSNR。这种改进既可以用于优化非易失性存储器(NVM)的使用,以在设备中存储生物信号的记录,也可以用于最小化整个信号传输的能量消耗及其某些特征。根据外部输入(例如患者),我们专门设计了传感阶段,以实现适合医疗保健(HC)和健康(WN)的信号质量。在本文中,我们设想了一种双操作可穿戴式心电监护仪,考虑了用于输入生物信号压缩的多核DSP和用于传输或本地存储的不同技术。实验结果表明了Rakeness方法的有效性(比基线节能高达约70%),并评估了考虑不同用例场景的能源收益。
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:604180095
Book学术官方微信