PHIDIAS: ultra-low-power holistic design for smart bio-signals computing platforms

Daniele Bortolotti, Andrea Bartolini, L. Benini, V. R. Pamula, N. V. Helleputte, C. Hoof, M. Verhelst, T. Gemmeke, Rubén Braojos Lopez, G. Ansaloni, David Atienza Alonso, P. Vandergheynst
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引用次数: 1

Abstract

Emerging and future HealthCare policies are fueling up an application-driven shift toward long-term monitoring of biosignals by means of embedded ultra-low power Wireless Body Sensor Networks (WBSNs). In order to break out, these applications needed the emergence of new technologies to allow the development of extremely power-efficient bio-sensing nodes. The PHIDIAS project aims at unlocking the development of ultra-low power bio-sensing WBSNs by tackling multiple and interlocking technological breakthroughs: (i) the development of new signal processing models and methods based on the recently proposed Compressive Sampling paradigm, which allows the design of energy-minimal computational architectures and analog front-ends, (ii) the efficient hardware implementation of components, both analog and digital, building upon an innovative ultra-low-power signal processing front-end, (iii) the evaluation of the global power reduction using a system wide integration of hardware and software components focused on compressed-sensing-based bio-signals analysis. PHIDIAS brought together a mixed consortium of academic and industrial research partners representing pan-European excellence in different fields impacting the energy-aware optimization of WBSNs, including experts in signal processing and digital/analog IC design. In this way, PHIDIAS pioneered a unique holistic approach, ensuring that key breakthroughs worked out in a cooperative way toward the global objective of the project.
PHIDIAS:超低功耗整体设计智能生物信号计算平台
新兴和未来的医疗保健政策正在推动一种应用驱动的转变,即通过嵌入式超低功耗无线身体传感器网络(WBSNs)对生物信号进行长期监测。为了突破,这些应用需要新技术的出现,以允许开发极其节能的生物传感节点。PHIDIAS项目旨在通过解决多个相互关联的技术突破,解锁超低功耗生物传感wbns的发展:(i)基于最近提出的压缩采样范式开发新的信号处理模型和方法,该范式允许设计能量最小的计算架构和模拟前端;(ii)基于创新的超低功耗信号处理前端的模拟和数字组件的高效硬件实现;(iii)利用以基于压缩传感的生物信号分析为重点的硬件和软件组件的系统广泛集成来评估全球功率降低。PHIDIAS汇集了一个学术和工业研究合作伙伴的混合联盟,代表了影响WBSNs节能优化的不同领域的泛欧卓越,包括信号处理和数字/模拟IC设计方面的专家。通过这种方式,PHIDIAS开创了一种独特的整体方法,确保关键突破以合作的方式实现项目的全球目标。
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