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dc.contributor.author
Mazzoni, Benedetta
dc.contributor.author
Tagliavini, Giuseppe
dc.contributor.author
Benini, Luca
dc.contributor.author
Benatti, Simone
dc.contributor.editor
Valle, Maurizio
dc.contributor.editor
Lehmhus, Dirk
dc.contributor.editor
Gianoglio, Christian
dc.contributor.editor
Ragusa, Edouardo
dc.contributor.editor
Seminara, Lucia
dc.contributor.editor
Bosse, Stefan
dc.contributor.editor
Ibrahim, Ali
dc.contributor.editor
Thoben, Klaus-Dieter
dc.date.accessioned
2022-10-04T11:18:02Z
dc.date.available
2022-10-04T08:44:02Z
dc.date.available
2022-10-04T11:18:02Z
dc.date.issued
2023
dc.identifier.isbn
978-3-031-16280-0
en_US
dc.identifier.isbn
978-3-031-16281-7
en_US
dc.identifier.issn
2367-3389
dc.identifier.issn
2367-3370
dc.identifier.other
10.1007/978-3-031-16281-7_16
en_US
dc.identifier.uri
http://hdl.handle.net/20.500.11850/574187
dc.description.abstract
The real-time detection of the R peaks of the ECG signal is crucial to provide information on cardiac functionality, and several strategies have been presented in the past. In this work, we adapt the classical Pan and Tompkins (PT) algorithm for efficient execution on low-power microcontroller (MCU) platforms to design a full-fledged heart rate detection system. We target a commercial MCU based on ARM Cortex-M4 and an ultra-low-power solution based on the RISC-V PULP platform. Experimental results show that our approach achieves an accuracy above 99.5%, comparable to the state-of-the-art solutions, and an energy efficiency that is one order of magnitude better than other software solutions.
en_US
dc.language.iso
en
en_US
dc.publisher
Springer
en_US
dc.subject
Egg
en_US
dc.subject
R peak
en_US
dc.subject
Heart rate
en_US
dc.subject
Low- power biosignal processing
en_US
dc.title
An Optimized Heart Rate Detection System Based onLow-Power Microcontroller Platforms forBiosignal Processing
en_US
dc.type
Conference Paper
dc.date.published
2022-09-04
ethz.book.title
Advances in System-Integrated Intelligence
en_US
ethz.journal.title
Lecture Notes in Networks and Systems
ethz.journal.volume
546
en_US
ethz.pages.start
160
en_US
ethz.pages.end
170
en_US
ethz.event
6th International Conference on System-Integrated Intelligence (SYSINT 2022)
en_US
ethz.event.location
Genova, Italy
en_US
ethz.event.date
September 7-9, 2022
en_US
ethz.grant
Pilot using Independent Local & Open Technologies
en_US
ethz.identifier.wos
ethz.publication.place
Cham
en_US
ethz.publication.status
published
en_US
ethz.leitzahl
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02140 - Dep. Inf.technologie und Elektrotechnik / Dep. of Inform.Technol. Electrical Eng.::02636 - Institut für Integrierte Systeme / Integrated Systems Laboratory::03996 - Benini, Luca / Benini, Luca
ethz.leitzahl
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02140 - Dep. Inf.technologie und Elektrotechnik / Dep. of Inform.Technol. Electrical Eng.::02636 - Institut für Integrierte Systeme / Integrated Systems Laboratory::03996 - Benini, Luca / Benini, Luca
ethz.leitzahl.certified
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02140 - Dep. Inf.technologie und Elektrotechnik / Dep. of Inform.Technol. Electrical Eng.::02636 - Institut für Integrierte Systeme / Integrated Systems Laboratory::03996 - Benini, Luca / Benini, Luca
ethz.grant.agreementno
101034126
ethz.grant.fundername
EC
ethz.grant.funderDoi
10.13039/501100000780
ethz.grant.program
H2020
ethz.date.deposited
2022-10-04T08:44:03Z
ethz.source
BATCH
ethz.eth
yes
en_US
ethz.availability
Metadata only
en_US
ethz.rosetta.installDate
2022-10-04T11:18:03Z
ethz.rosetta.lastUpdated
2024-02-02T18:23:09Z
ethz.rosetta.versionExported
true
ethz.COinS
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