Journal article Open Access

Resource-Aware Distributed Epilepsy Monitoring Using Self-Awareness From Edge to Cloud

Forooghifar, Farnaz; Aminifar, Amir; Atienza Alonso, David

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<identifier identifierType="URL">https://zenodo.org/record/3903306</identifier>
<creators>
<creator>
<creatorName>Forooghifar, Farnaz</creatorName>
<givenName>Farnaz</givenName>
<familyName>Forooghifar</familyName>
<affiliation>EPFL</affiliation>
</creator>
<creator>
<creatorName>Aminifar, Amir</creatorName>
<givenName>Amir</givenName>
<familyName>Aminifar</familyName>
<affiliation>EPFL</affiliation>
</creator>
<creator>
<creatorName>Atienza Alonso, David</creatorName>
<givenName>David</givenName>
<familyName>Atienza Alonso</familyName>
<affiliation>EPFL</affiliation>
</creator>
</creators>
<titles>
<title>Resource-Aware Distributed Epilepsy Monitoring Using Self-Awareness From Edge to Cloud</title>
</titles>
<publisher>Zenodo</publisher>
<publicationYear>2019</publicationYear>
<dates>
<date dateType="Issued">2019-11-04</date>
</dates>
<resourceType resourceTypeGeneral="Text">Journal article</resourceType>
<alternateIdentifiers>
<alternateIdentifier alternateIdentifierType="url">https://zenodo.org/record/3903306</alternateIdentifier>
</alternateIdentifiers>
<relatedIdentifiers>
<relatedIdentifier relatedIdentifierType="DOI" relationType="IsIdenticalTo">10.1109/TBCAS.2019.2951222</relatedIdentifier>
<relatedIdentifier relatedIdentifierType="URL" relationType="IsPartOf">https://zenodo.org/communities/deephealth</relatedIdentifier>
</relatedIdentifiers>
<rightsList>
<rights rightsURI="info:eu-repo/semantics/openAccess">Open Access</rights>
</rightsList>
<descriptions>
<description descriptionType="Abstract">&lt;p&gt;The integration of wearable devices in humans&amp;#39; daily lives has grown significantly in recent years and still continues to affect different aspects of high-quality life. Thus, ensuring the reliability of the decisions becomes essential in biomedical applications, while representing a major challenge considering battery-powered wearable technologies. Transferring the complex and energy-consuming computations to fogs or clouds can significantly reduce the energy consumption of wearable devices and result in a longer lifetime of these systems with a single battery charge. In this work, we aim to distribute the complex and energy-consuming machine-learning computations between the edge, fog, and cloud, based on the notion of self-awareness that takes into account the complexity and reliability of the algorithm. We also model and analyze the trade-offs in terms of energy consumption, latency, and performance of different Internet of Things (IoT) solutions. We consider the epileptic seizure detection problem as our real-world case study to demonstrate the importance of our proposed self-aware methodology.&lt;/p&gt;</description>
</descriptions>
<fundingReferences>
<fundingReference>
<funderName>European Commission</funderName>
<funderIdentifier funderIdentifierType="Crossref Funder ID">10.13039/501100000780</funderIdentifier>
<awardNumber awardURI="info:eu-repo/grantAgreement/EC/H2020/825111/">825111</awardNumber>
<awardTitle>Deep-Learning and HPC to Boost Biomedical Applications for Health</awardTitle>
</fundingReference>
<fundingReference>
<funderName>European Commission</funderName>
<funderIdentifier funderIdentifierType="Crossref Funder ID">10.13039/501100000780</funderIdentifier>
<awardNumber awardURI="info:eu-repo/grantAgreement/EC/H2020/785907/">785907</awardNumber>
<awardTitle>Human Brain Project Specific Grant Agreement 2</awardTitle>
</fundingReference>
<fundingReference>
<funderName>Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung</funderName>
<funderIdentifier funderIdentifierType="Crossref Funder ID">10.13039/501100001711</funderIdentifier>
<awardNumber awardURI="info:eu-repo/grantAgreement/SNSF/Project+funding/200020_182009/">200020_182009</awardNumber>
<awardTitle>ML-edge: Enabling Machine-Learning-Based Health Monitoring in Edge Sensors via Architectural Customization</awardTitle>
</fundingReference>
</fundingReferences>
</resource>

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