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dc.contributor.authorDisi, Mohammed Al
dc.contributor.authorDjelouat, Hamza
dc.contributor.authorKotronis, Christos
dc.contributor.authorPolitis, Elena
dc.contributor.authorAmira, Abbes
dc.contributor.authorBensaali, Faycal
dc.contributor.authorDimitrakopoulos, George
dc.contributor.authorAlinier, Guillaume
dc.date.accessioned2018-12-21T15:03:49Z
dc.date.available2018-12-21T15:03:49Z
dc.date.issued2018-10-23
dc.identifier.citationDisi , M A , Djelouat , H , Kotronis , C , Politis , E , Amira , A , Bensaali , F , Dimitrakopoulos , G & Alinier , G 2018 , ' ECG Signal Reconstruction on the IoT-Gateway and Efficacy of Compressive Sensing Under Real-time Constraints ' , IEEE Access , vol. 6 , 8502753 , pp. 69130-69140 . https://doi.org/10.1109/ACCESS.2018.2877679
dc.identifier.issn2169-3536
dc.identifier.otherPURE: 15712115
dc.identifier.otherPURE UUID: 7ff2c7ef-5bbd-4334-8d98-c8e7ab3d5218
dc.identifier.otherScopus: 85055675268
dc.identifier.urihttp://hdl.handle.net/2299/20900
dc.description.abstractRemote health monitoring is becoming indispensable, though, Internet of Things (IoTs)-based solutions have many implementation challenges, including energy consumption at the sensing node, and delay and instability due to cloud computing. Compressive sensing (CS) has been explored as a method to extend the battery lifetime of medical wearable devices. However, it is usually associated with computational complexity at the decoding end, increasing the latency of the system. Meanwhile, mobile processors are becoming computationally stronger and more efficient. Heterogeneous multicore platforms (HMPs) offer a local processing solution that can alleviate the limitations of remote signal processing. This paper demonstrates the real-time performance of compressed ECG reconstruction on ARM's big.LITTLE HMP and the advantages they provide as the primary processing unit of the IoT architecture. It also investigates the efficacy of CS in minimizing power consumption of a wearable device under real-time and hardware constraints. Results show that both the orthogonal matching pursuit and subspace pursuit reconstruction algorithms can be executed on the platform in real time and yield optimum performance on a single A15 core at minimum frequency. The CS extends the battery life of wearable medical devices up to 15.4% considering ECGs suitable for wellness applications and up to 6.6% for clinical grade ECGs. Energy consumption at the gateway is largely due to an active internet connection; hence, processing the signals locally both mitigates system's latency and improves gateway's battery life. Many remote health solutions can benefit from an architecture centered around the use of HMPs, a step toward better remote health monitoring systems.en
dc.format.extent11
dc.language.isoeng
dc.relation.ispartofIEEE Access
dc.rights/dk/atira/pure/core/openaccesspermission/open
dc.subjectBiomedical monitoring
dc.subjectcompressed sensing
dc.subjectConnected health
dc.subjectElectrocardiography
dc.subjectEnergy consumption
dc.subjectenergy efficiency
dc.subjectheterogeneous multicore platforms
dc.subjectinternet of things
dc.subjectLogic gates
dc.subjectmobile real-time health monitoring
dc.subjectMonitoring
dc.subjectmulticore processing
dc.subjectReal-time systems
dc.subjectremote monitoring
dc.subjectSensors
dc.subjectwearable sensors
dc.subjectComputer Science(all)
dc.subjectMaterials Science(all)
dc.subjectEngineering(all)
dc.titleECG Signal Reconstruction on the IoT-Gateway and Efficacy of Compressive Sensing Under Real-time Constraintsen
dc.contributor.institutionUniversity of Hertfordshire
dc.description.statusPeer reviewed
dc.identifier.urlhttp://www.scopus.com/inward/record.url?scp=85055675268&partnerID=8YFLogxK
dc.description.versiontypeFinal Published version
dcterms.dateAccepted2018-01-01
rioxxterms.versionVoR
rioxxterms.versionofrecordhttps://doi.org/10.1109/ACCESS.2018.2877679
rioxxterms.licenseref.urihttp://creativecommons.org/licenses/by/4.0/
rioxxterms.typeJournal Article/Review
herts.preservation.rarelyaccessedtrue
herts.rights.accesstypeopenAccess


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