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
{"title":"PHIDIAS:超低功耗整体设计智能生物信号计算平台","authors":"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","doi":"10.1145/2903150.2903469","DOIUrl":null,"url":null,"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.","PeriodicalId":226569,"journal":{"name":"Proceedings of the ACM International Conference on Computing Frontiers","volume":"183 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"PHIDIAS: ultra-low-power holistic design for smart bio-signals computing platforms\",\"authors\":\"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\",\"doi\":\"10.1145/2903150.2903469\",\"DOIUrl\":null,\"url\":null,\"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.\",\"PeriodicalId\":226569,\"journal\":{\"name\":\"Proceedings of the ACM International Conference on Computing Frontiers\",\"volume\":\"183 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-05-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the ACM International Conference on Computing Frontiers\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/2903150.2903469\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the ACM International Conference on Computing Frontiers","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2903150.2903469","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
PHIDIAS: ultra-low-power holistic design for smart bio-signals computing platforms
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.